text:
Poverty Duration in Denmark Mohammad Azhar Hussain - SFI
Poverty Duration in Denmark
Mohammad Azhar Hussain
Welfare Distribution
Working Paper 28:2002
Working Paper
The Danish National Institute of Social Research
Poverty Duration in Denmark
Mohammad Azhar Hussain *
Abstract: The total number of years in poverty over an 11-year period is simulated for Danes
entering poverty between 1981-1987. The basis for simulations is exit rates from poverty and reentry
rates in to poverty, which are estimated in the paper. To measure the sensitivity of applying
a single spell or a multiple spell approach both approaches are implemented and compared to
the actual distribution of total years spent in poverty. The sensitivity of results with respect to
left-censored spells is also investigated. Unobserved heterogeneity is accounted for by a discrete
distribution with two support points. It is found that the multiple spells approach clearly
outperforms the single spell approach. Ignoring unobserved heterogeneity or including left
censored poverty spells does not imply much less precise estimates of the distribution of years in
poverty or average poverty duration.
JEL code: C14, C23, C25, I32, J64
Key words: Poverty, duration, low inc ome, multiple spells, exit rate, re-entry rate, simulation,
unobserved heterogeneity, right censoring, left censoring
Acknowledgements: I am grateful to Nina Smith and Tor Eriksson for very useful comments and suggestions. All
remaining errors are mine.
?? Department of Economics, The Aarhus School of Business, DK-8210 Aarhus V, Denmark, and CIM, CLS
and SFI. E-mail: firstname.lastname@example.com
1. Introduction
Earlier research on poverty has mainly focused on the short-term incidence of poverty, e.g. the
fraction of people under the poverty threshold. With the emergence of panel data, researchers are
now concentrating more on the dynamics of poverty and the duration of poverty. This is
important because static poverty can be very misleading, when the burden of poverty on
individuals is analysed. The group of poor could be very mobile, so that a person is only poor for
a short while and then leaves poverty for a long time, implying that poverty is a transitory
phenomenon. Alternatively, poverty could be long-term, with low escape probability, which
means that the poor individuals stay in poverty for a long time: This is a bigger problem. An
uneven distribution of poverty, with only a small fraction of individuals being affected and the
greater part unaffected, implies that the major part of society never experiences poverty, which
can threaten cohesion and political support for people with low incomes. Further, repeated
poverty spells are usually not counted for, implying that poverty over a given time period could
be longer than a single spell approach would show. The aim of this paper is to model the duration
of poverty spells for individuals in Denmark from 1981 to 1997, by applying a multivariate
model to quantify the factors that influence the duration of poverty.
The paper is an extension of previous Danish research on poverty in different ways. First,
multiple spells are taken into account and thereby a more accurate measure of total time being
poor is possible. This is done by estimation of exit and re-entry rates, and then using these rates
to estimate the distribution of years in poverty. Second, a multivariate approach is followed, so
that the effect of different demographic and labour market variables can be estimated.
The next Section is a review of previous research on poverty persistence. Section three presents
the econometric model. The fourth Section deals with data and issues of poverty thresholds,
while Section five presents results from estimation and simulations. The last Section concludes.
2. Earlier research
There is some variation in the modelling of poverty durations. Early studies used non-parametric
methods, e.g. calculated the number of years in poverty in a given time span, see Duncan (1983),
and Duncan and Rodgers (1991). This approach ignores that a person ending (starting) a poverty
spell, maybe is only in the beginning (ending) of a long spell of poverty, although only one or
two years are observed. Long poverty spells are thus underestimated, because some of the short
term poor are left- or right-censored. Right-censored cases are easily handled, while a proper
modelling of left-censored spells is less frequent. Moffitt and Rendall (1995) model left-censored
spells, but only by including variables, whose values are known back in time (age and calendar
Bane and Ellwood (1986) take the right-censored cases into account and use a spell-based
approach to estimate mean spell durations for different kinds of spell beginning events. However,
their study is mainly concerned with single spells, which is far from sufficient when analysing
poverty duration. Stevens (1994) updates Bane and Ellwood by including an additional six years
of the PSID. A probit model is applied to estimate exit rates from poverty, controlling for year
and business cycle effects. The model allows for duration dependence in the hazard rate. The
analysis is extended further by focusing on multiple spells and concludes that this is important,
because persons ending a long poverty spell are more likely to re-enter poverty.
Devicienti (2000) uses a log-log model and defines a discrete time hazard rate h ij
for person i to
leave poverty (and non-poverty) in time interval j as
hij ( Xij
) ? 1?
exp[ ? exp( Xij? ? ? ( d))]
where X is a set of explanatory variables, ? is the set of parameters to be estimated, and ? is a
functional form specifying how the hazard rate changes with duration (d) of poverty. To avoid
constraints on ? , a fully flexible specification is used by introducing interval (year) specific
dummies for the baseline hazard. Apart from the hazard specification and omitted modelling of
unobserved heterogeneity, his study is very much like Stevens (1999).
Stevens (1999) uses a multivariate approach when estimating the poverty duration, taking
multiple poverty and non-poverty spells into account. The multivariate approach increases the
understanding of the factors influencing poverty duration. A discrete time hazard framework
accounts for multiple spells, and the framework is used to derive estimates of total time being
poor. The treatment of poverty duration is advanced since issues concerning multiple spells, leftand
right-censoring and heterogeneity are all addressed as described below. Stevens approach is
also used in this paper.
Focusing on the duration of poverty means that other important poverty issues are not addressed
in such detail. This is true for the severity of poverty, traditionally measured by the distance from
the poverty line to the income level of an individual, and inequality among the poor. An index
simultaneously taking several dimensions, but duration, into account is the index in Sen (1976).
However, severity in another sense may be included. Combining the traditional way of measuring
severity and duration is proposed in Nicholson (1979) as
p = sev*dur
where p is a poverty measure (burden), sev is severity and dur is duration of a poverty spell.
When the number of poor years is simply counted, then sev is implicitly assumed to equal 1, so
persons are counted equally poor whether they are just below the poverty line or have an income
equal to half the poverty line. If instead sev is properly included, then a person with income equal
to ¼ of the poverty line for one year (dur=1) will effectively be counted as having 4 years in
poverty, whereas a person having income equal to the poverty line will be counted as having 1
year of poverty. However, the approach is not followed here, because the focus is on the duration
of poverty and not its intensity.
Danish contributions to the poverty duration literature are mainly contained in Pedersen and
Smith (1998). Poverty exit probabilities are estimated and durations are derived from them. Their
study thus follows the single spell approach and the re-entry into poverty is therefore not taken
into account. Othe r Danish studies are primarily concerned with the cross-sectional calculation of
poverty rates, see e.g. Ministry of Economic Affairs (1993).
3. Econometric model
Define e s
as the exit probability from poverty after s years of poverty and r s
as the re-entry
probability from non-poverty after s years of non-poverty. The probability of experiencing a
completed poverty spell T with duration d is then:
? ?
P T ? d ? f d ? ?? ? 1
) ( ) (1 ? e s
)? ed
( (2)
where the first term is the probability of not exiting poverty up to time d-1. The probability of a
d- years non-poverty spell is defined analogously
? ?
g d ? ?? ? 1
) (1 ? r s
)? rd
( (3)
The probability of observing a right-censored poverty spell is
P( T ? d ) ? 1?
T ? d)
? 1?
d ) ? (1 ? )
e s
and the probability of observing a right-censored non-poverty spell is
P( T ? d)
? 1?
? (1 ? )
r s
where F and G are the cumulative density functions for poverty and non-poverty durations. In the
spell based approach right-censored spells are thus easily incorporated.
The probability of transition in or out of poverty depends on personal characteristics X it
. Together
with duration terms this gives a model for poverty duration. But apart from observable
characteristics X it
there can be unobservable characteristics that create dependence among
individuals' exit probabilities across time. For instance persons with a long poverty spell in the
past might be more likely to re-enter poverty or, persons with low exit rates might also have high
re-entry rates. Ignoring unobserved heterogeneity, can thus bias estimated parameters, e.g.
overstate the effect of explanatory variables on the hazard rate, see Lancaster (1990). Here,
unobserved heterogeneity among individuals is modelled as in Eberwein et al. (1997) and
Stevens (1999), whose specification allows correlation across individual spells in and out of
poverty, and at the same time allows the heterogeneity to enter both poverty spells as well as nonpoverty
spells through the intercept terms. Using a logistic specification, the exit and re-entry
rates are defined as
p p p
exp( ?
? ?
? (6)
exp( ? ? ? ? ? X )
n n n
exp( ?
? ?
? (7)
exp( ? ? ? ? ? X )
? and ? are individual specific effects of type j for person i during poverty spells (p)
and non-poverty spells (n), ? and ? are duration dummies for spell lengths d and ? and ?
are effects of background variables.
? and ? are chosen to have discrete distributions with two support points each (j=2), so that
there are two types of poverty spell,
? and p 1 ? 2
(i subscript suppressed), and two types of nonpoverty
? and n 1 ? . This gives four possible types of person: With probability
the person
is of type ( p n p n
p n
? ,
1 ? ), (
1 ? ,
1 ? ) has probability
, (? ,
2 ? ) has probability
and a person has
probability P 4
of being of type (? ,? ). Each individual is of either type with some probability,
so P 1
=1. With this specification heterogeneity implies having the combination of
high or low exit probability and high or low re-entry probability. Each individual is characterized
by a vector containing heterogeneity terms
likelihood of being of type l, l={1,2,3,4}, is
p n p n p n p n
? = [(? ,? ),( ? ,? ),(? ,? ),( ? ,? )]. The
Li( ?
i, l
) ? ? fis(
? gis(
[1 ? Fi
( d,
)] [1 ? Gi(
? s?
1 ??
1 ?
where ?=1 if a person's last spell ends in poverty, and ?=0, if it ends with non-poverty. n i
and m i
are numbers of poverty and non-poverty spells. Each individual has some probability of being of
either type, so individual i's contribution to the likelihood function is
? )
i( i,
Maximising the likelihood in (9) produces estimates for P, ? , ? and ?.
4. Data sources and definition of poverty
The data used in the analysis stem from administrative registers in Statistics Denmark. Further
documentation on the data may be found on www.cls.dk. It is a longitudinal ½ percent
representative unbalanced panel data set of the Danish population for the years 1976-1997. The
data set contains information on demographic, educational, income and labour market variables.
There is no standard way of proceeding with analysis of an equivalent income measure. Thus,
there is some variation in defining needs, which income or tax components to include, the unit of
calculation and the accounting period. In this study the income concept is equivalent annual
family income after transfers and taxes (EDI). Its calculated from EDI=DI/ES, where ES is the
equivalence scale and DI is family disposable income defined as the sum of total family gross
income minus total family taxes. Only individuals with positive EDI are included.
Gross income is the sum of labour earnings, asset flows, imputed value of owner-occupied
housing, private transfers and public transfers such as sickness benefits, unemployment insurance
benefits, pensions and social assistance. Asset flows include income from rent, interest and
dividends. Public non-taxable transfers such as housing benefits and individual supplementary
means-tested benefits for pensioners are not included. As these benefits are targeted at the bottom
of the income distribution (primarily first and second deciles for housing benefits, see Danish
Economic Council, 2001) this might overstate the percentage in poverty. Conversely the
consequence is also a downward biased poverty line, so the total effect of excluding these
benefits is not clear. Further, non-public transfers between separated parents of a child are not
In this paper ES is the sum of discrete weights attached to each individual in a family, the socalled
new OECD equivalence scales. The first adult receives the weight 1, the second has a
weight of 0.7 and children weigh 0.5 each, see Pedersen and Smith (1998) for an application of
similar weights. Each individual in the family is "given" the same EDI, which leads to the
implicit assumption that resources are equally distributed among the family members. This
assumption can lead to biased poverty estimates for children, women or men, if different intrafamily
distribution systems are actually applied, see Findlay and Wright (1996).
Recent international comparisons of poverty and inequality discuss equivalence scale choice and
implications, see Förster (1995), Atkinson et al. (1995) and Buhmann et al. (1988), whose overall
conclusion is that the ranking of countries is generally maintained when altering the equivalence
scale. On German and American data, Burkhauser et al. (1996) do not find poverty and inequality
rates to be sensitive to the equivalence scale choices. The insensitivity no longer seems to hold
when the equivalence scales are income level dependent, see Aaberge and Melby (1998).
There is not much consensus about the appropriate poverty line and the implicit poverty lines in
the different countries differ. Gustafsson (1995) examines the quantitative poverty measurement
literature. In Denmark there is no officially defined absolute poverty line. The relative growth of
public individual transfers (e.g. pensions, unemployment benefit and means-tested transfers)
follows the relative growth in hourly labour wages. This implies that Denmark implicitly has a
relative poverty line, which does not only account for price increases but also for increases in
productivity. In contrast the official American poverty line is absolute, so that changes only occur
due to price changes and not due to productivity gains. In this study the 50% of median EDI is
applied. Other studies use the 40% cut-off to define severe poverty or the 60% cut-off to define
low income or other cut-offs are used as a sensitivity analysis tool. Using the 40% poverty line
will give lower poverty rate estimates, while the 60% poverty line will give higher poverty rates.
As income distributions are rightly skewed the median is less than the mean, so poverty lines and
poverty rates based on the median are lower than when based on the mean. For applications of
poverty lines other than the one employed here, see e.g. Bishop et al (1999), Hauser and Fabig
(1999), and Gallie and Paugam (2000).
Table 1. Table 1. Poverty lines, 1981-1997, Danish Kroner
1981 27,717
1982 31,514
1983 33,219
1984 35,306
1985 37,645
1986 39,480
1987 42,500
1988 45,000
1989 47,000
1990 49,412
1991 49,500
1992 50,588
1993 51,176
1994 54,545
1995 57,000
1996 59,706
1997 62,045
Absolute growth 1981-1997 34,328
- Annual growth 2,146
Percentage Growth 1981-1997, % 123.8
- Annual growth, % 5.2
Using 50% of median, the poverty line was 27,700 DKK in 1981 and 62,000 DKK in 1997, see
Table 1. The poverty line's annual growth rate is 5.2% (2,146 DKK).
Individuals with equivalent income below the poverty line in a given year are classified as poor,
while individuals with equivalent income above the poverty line are classified as non-poor.
Denmark is one of the Scandinavian welfare states, implying relatively high social transfers over
long periods. "Poor" may therefore be a misleading characterization of Danes with low incomes
because these low-income people will probably all have access to basic human needs (food,
clothing and shelter). Instead, these people are relatively poor, meaning that they are not able to
maintain the standard of living that the main part of Danes are able to maintain. Nevertheless, the
term "poor" is used in the following, because the literature often uses this term to characterize
people at the bottom of the income distribution.
The unit of analysis is the individual, although the household is the unit of calculation. The
household consists of one or two adults and children less than 18 years of age living with an
adult. For Denmark, it has not been possible to pool the income of cohabiting partners, because
income only exists for both partners if they are married. Children over 18-years of age living with
an adult are treated as singles. This will tend to overstate the estimated proportion living under
the poverty threshold.
The aggregate unemployment rate used in the estimations is not from the CLS database, but
instead it is the official annual figure from Statistics Denmark. The rate is defined as the
registered unemployed divided by the work force, which consists of the registered unemployed
and people in employment.
Data are present since 1980, but to avoid modelling left-censored spells, only people starting a
poverty spell in a year after 1980, are included, see Stevens (1999) and Devicienti (2000). So in
the first year of the 12-year period, the individual is non-poor and in the second year the
individual is poor. Therefore 11 years is the maximum number of years in poverty. Using this
method could have allowed a maximum of 17 years (1981-1997), but this would reduce the
number of observations, because fewer individuals are present for longer periods. The chosen 12
years is thus a compromise between sample size and the size of the observation window.
The subpopulation analysed in this paper consists of all persons aged 18-74 years who were
present in 12 consecutive years between 1980 and 1997. Data is thus a balanced panel containing
6,072 person-years or 552 persons. Individuals who do not have a complete 12-year sequence are
excluded from the analysis. To each poverty or non-poverty spell a vector of constant or time
varying demographic and labour market variables is attached. Some variables are included as
dummies and others in continuous form.
Although the lower age limit is 18 years, there are probably not many students included in the
sample, since only initially non-poor and then poor individuals are included. As students often
have low incomes, they will not meet the first criterion.
In order not to complicate estimations further, the initial conditions problem is not addressed in
this paper, although it is present, because of the conditions that the individual is non-poor in the
first year and poor in the second year of the 12-year period, see Heckman (1981).
Sample statistics are presented in Table A1 in the Appendix.
5. Estimation results
5.1. Aggregate exit and re-entry probabilities (only duration terms included)
Simple aggregate measures of exit and re-entry rates are obtained by only controlling for the
duration of poverty and non-poverty. Using the logit framework by maximizing the likelihood in
(9), but only with the presence of duration dummies
? and
? , so
e ijdt
exp( ?
? and
exp( ? )
r ijdt
exp( ?
exp( ? )
gives the estimates in Table 2. The exit and re-entry rates are calculated from the estimated
parameters by transforming back the logit estimates.
Table 2. Exit and re-entry parameter estimates and hazard rates of poverty and nonpoverty
spells. ML-estimation of (9), but only with duration dummies included
Duration (d), years
(? )
(e d )
(? )
1 -0.0121 0.0649 0.4970 -1.5699 0.0928 0.1722
2 -0.3271 0.0949 0.4189 -2.1773 0.1276 0.1018
3 -0.7062 0.1323 0.3304 -2.6613 0.1660 0.0653
4 -0.7234 0.1651 0.3266 -2.8111 0.1868 0.0567
5 -0.4326 0.2009 0.3935 -3.7425 0.1941 0.0231
6 -0.8728 0.2615 0.2947 -3.3103 0.2505 0.0352
7 -1.4685 0.3036 0.1872 -3.7508 0.3154 0.0230
8 -1.2766 0.4286 0.2181 -3.2340 0.2268 0.0379
9 -1.8778 0.6960 0.1326 -3.8421 0.3614 0.0210
10 -2.2970 0.9461 0.0914
Log likelihood -2,324.3
(r d )
All parameters, but one (poverty duration after 1 year), are highly significant. The logit estimates
implies that the probability of exiting poverty after one year of poverty is 49.7%, but after two
years of poverty the exit chance is reduced to 41.9%, and after 10 years of poverty there is a
much lower chance of escape (9.1%). The probability of re-entry into poverty from non-poverty
is 17.2% after one year in non-poverty, but only 2.1% after 9 years out of poverty. Thus escaping
poverty becomes more difficult the longer is the poverty spell and re-entering poverty is more
likely the shorter is the non-poverty spell. The cause of this negative duration dependence or state
dependence could be loss of motivation, loss of self-confidence or changing attitudes and
behaviour over time in response to being in the poor state and perhaps receiving social benefit.
This could make it more difficult to escape poverty if the poor for instance reduce job search
efforts. However, the calculations do not include any explanatory variables, which means that the
observed negative duration dependence could be caused by different characteristics among the
individuals, which is not modelled in Table 2.
Pedersen and Smith (1998) find 1-year exit rates for Denmark in the interval 75 to 90%, which is
much higher than reported here. This difference in hazard rates could be caused by Pedersen and
Smith's data, which are an unbalanced sample containing a mixture of recent entrants and longterm
poor, while the figures in Table 2 are based on a more homogeneous population, with
hazard rates calculated for persons with the same duration of poverty or non-poverty. Pedersen
and Smith's estimate of average poverty duration is also much smaller (1.25 years), as compared
to 3.3 years in Table 3. In contrast, their exit rates are close to the ones in Table 2.
The declining hazard of exiting poverty or non-poverty is usually observed in duration analysis,
see e.g. Hill et al. (1998) concerning American individuals in young adulthood, Stevens (1999)
and Devicienti (2000). On American data Stevens (1999) estimates a poverty exit chance of 53%
after one year, 22% after 5 years, but only 11% after 10 years, while Devicienti (2000) with UK
data has an exit rate of 41% after 1 year and 6% after 5 years. At the same time re-entry rates into
poverty are lower in Denmark (17% after 1 year, and 2% after 5 years), while they are very
similar in the UK (27% after 1 year, and 7% after 5 years) and the USA (27% after 1 year, and
8% after 5 years). Comparing the exit and re-entry rates implies a higher UK poverty persistence
than in Denmark and the USA, and the average number of years in poverty can be expected to be
the highest in the UK and the lowest in Denmark.
The exit rates in Table 2 can be used to estimate the number of years spent in poverty during an
11-year period, if a person enters poverty in the first year of the period, in the following way
(single spell approach). After 1 year of poverty 49.7% leave poverty, so 49.7% of the sample
have a poverty of 1 year out of 11 years, under the assumption that they do not re-enter poverty in
the 11-year period. In the beginning of year 2, 50.3% of the original sample is left (1 minus exit
rate at year 1), and after two years of poverty 41.9% will escape poverty, thus
0.419x0.503=21.1% have two years of poverty. Continuing in this way, the fraction of people
who are poor for d years with the single spell approach is
? 1
(1 ? e s
e ) , d={1,2,3, … }
where e s
is the exit probability after s years of poverty. The distribution according to duration in
the multiple spell approach is more complicated and is explained in Paragraph 5.2. Briefly, it is
worth noting, that re-entry is assumed possible in the multiple spells approach, which is in
contrast to the single spell approach, where only one spell for each individual is assumed.
Table 3. Distribution of years poor out of the next 11 years, if initially poor, %
Duration, years Single spell approach Multiple spells approach Actual
1 49.7 28.3 27.9
2 21.1 19.6 22.8
3 9.7 13.9 11.8
4 6.4 10.2 12.5
5 5.2 8.6 8.0
6 2.4 6.0 4.7
7 1.1 4.2 2.7
8 1.0 3.0 4.0
9 0.5 2.0 2.2
10 0.3 1.4 1.6
11 2.8 2.8 1.8
100 100 100
Average duration, years 2.4 3.5 3.3
Note: For single and multiple spells, 11 years duration actually represents durations of 11 years or more.
Using only the exit rates and not taking into account that people leaving poverty also sometimes
re-enter poverty, gives the figures in column 2 in Table 3. Compared to the actual distribution,
the single spell approach has approximately double the fraction of poor in one year. Generally,
lower chances of higher poverty durations implies that average duration for people entering
poverty is 2.4 years, compared to the actual 3.3 years. The single spell approach thus
underestimates the total time spent under the poverty line because it ignores that some individuals
experience multiple spells of poverty. Column 3 takes re-entry into account, giving a poverty
distribution that is much closer to the actual distribution of people entering poverty. One year of
poverty is almost the same as in the actual distribution and the same is true for the average
duration, which is estimated to be 3.5 years.
There has been some debate about whether poverty is a static phenomenon or whether there is
mobility in the income distribution, so that the same individuals are not always poor. Although
Table 3 does not answer this question, it is nevertheless clear that only about ¼ of individuals
entering poverty do not re-enter poverty in the next 10 years, implying ¾ will experience more
than a year in poverty. There is thus some tendency that poverty hits people who have been hit by
poverty in the past.
Applying the single spell approach clearly illustrates that the poverty distribution will be much
less precise and the average poverty duration will be unde restimated. This is true for Denmark as
well for the USA and the UK, see Table 4. For the three countries the preciseness of the two
approaches are measured by the mean of squared differences between the actual and the
estimated distribution of years in poverty. In all three countries the multiple spells approach is
much more accurate than the single spell approach. Mean square error for the distribution of
years in poverty is between 50 and 213 for the single spell approach and less than 18 for the
multiple spells approach.
Table 4. Comparison of single spell and multiple spells approaches to actual poverty
measures (distribution of years poor, average duration) in Denmark, the USA and the UK
(10 years)
Stevens (1999)
(6 years)
Devicienti (2000)
(11 years)
Table 2
Mean square error 1)
Single spell approach 65.7 212.9 50.1
Multiple spells approach 17.8 11.4 2.4
Average duration, years
Actual 4.0 3.1 3.3
Single spell approach 2.7 2.2 2.4
Multiple spells approach 4.4 3.0 3.5
1 c c 2
? Ai
) , where X i is the fraction with i years of poverty in a n c years period (10, 6 or 11) in country c (USA, UK or
Denmark). X is type of approach (Single spell or Multiple spells) and A is the actual distribution.
The average poverty duration is underestimated in all countries, when using the single spell
approach, whereas the multiple spells approach more accurately estimates the average duration.
Poverty duration for people entering poverty over a specified period is greater in the UK (51% or
3.1 years out of maximum 6 years) than in the US (40%) and Denmark (30%). Krause (1998)
examines poverty issues for Germany and presents the distribution of years in poverty for 1984-
1994. From his figures the average poverty duration is calculated to be 3.4 years or 31% of
maximum 11 years, which is close to the neighbouring Denmark. The higher average poverty in
the UK is perhaps surprising, because the European countries are usually expected to have a
better social safety net than in the USA. A reason for the ranking could be that the USA results
are based on an absolute poverty line, which is about 40% of median income, cf. Burkhauser et
al. (1995), while a relative poverty line defined as 50% of contemporaneous median equivalent
income is used for Denmark and 50% of mean equivalent income is used for the UK and
Germany. But the higher average for the UK very well reflects the international ranking of the
exit and re-entry rates mentioned earlier.
In Table 2, the duration term is included in a dummy form, e.g. a fully flexible specification
without imposing any structure on how the hazard rates depend on elapsed time since the start of
a spell. Estimation was also tried with including the duration in continuous form (d) together with
a cubic term (d 2 ) and an intercept (? ), implying exit and re-entry rates defined as (see also (1) for
a parametric representation of duration dependence):
p p 2
exp( ?
? ?
? ?
? and
p p 2
exp( ? ? ? d ? ? d )
n n 2
exp( ?
? ?
? ?
n n 2
exp( ? ? ? d ? ? d )
These regressions show significant negative duration dependence ( ? =-0.2657,
SE[ ? ]=0.0816, ? =0.9205, SE[ ? ]=0.9704, and ? =-0.7112, SE[ ? ]=0.1085, ? =4.6937,
? ]=1.2577), with the best fit for the re-entry rates (predicted re-entry rates close to actual
re-entry rates). Making the same simulations as in Table 3 shows the same average duration (3.5
years), but the distribution of years in poverty is slightly different with greater weights to longer
5.2. Estimation with unobserved heterogeneity
In order to explain poverty duration more fully, the determinants of poverty (non-poverty) spell
beginnings and poverty (non-poverty) spell endings are found by introducing further variables in
the estimation. Apart from duration variables and heterogeneity terms, the following are included
(sample statistics are presented in Appendix):
- Gender: Male (reference), female
- Age: under 30 years (reference), 30-39 years, 40-49 years, 50-59 years and 60+ years
- Indicator for being single: Single, couple (reference)
- Number of children
- Education: Number of years of schooling
- Hours of work per year: Divided by 100
- Aggregate unemployment rate: Percent of workforce unemployed
As all duration dummies are included, normalization for the heterogeneity terms is required, so
that only two heterogeneity parameters are estimated. Here
Maximizing the likelihood in (9) gives the parameter estimates in Table 5.
? and
? are normalised to zero.
The heterogeneity term for poverty spells,
? , is highly significant, whereas the heterogeneity
term for non-poverty spells, ? , shows less significance. About 29%
) of the population has
favourable unobserved characteristics, implying a much higher exit rate from poverty (logit of
0.9592) and a much lower re-entry rate into poverty (logit of –2.4322). 32% of the population has
very unfavourable unobserved characteristics, so they have low exit rates and high re-entry rates.
39% of the population has high exit rates, but also low re-entry rates, and almost none (0.01%)
has low exit rates and high re-entry rates. The consequences of poverty persistence for the two
middle heterogeneity cases are thus not clear when only looking at estimated parameters alone.
This is one reason for simulating distributions of years in poverty, which is the topic of the next
For Whites in the United States, Stevens (1999) has the same signs for the heterogeneity terms,
but with higher magnitudes and lower standard errors. In her estimations 96% of individuals are
characterized by high exit rates and low re-entry rates and 4% have low exit rates and high reentry
rates. There are almost none in the intermediate two cases. Devicienti (2000) does not
model heterogeneity.
Negative duration dependence in the re-entry rates is still present when controlling for other
variables. Except after 1 year and after 5 years of poverty, all exit rates are insignificant. This is
not surprising, because economic and demographic variables are now controlled for, implying
that the observed negative duration dependence in Table 2 is partly due to heterogeneity among
individuals: Those with higher hazards tend to leave poverty before those with low hazards,
leaving a group increasingly made up of low hazard people. Since we can only estimate the
hazard rate at time t for those who still have a chance of leaving poverty, the estimated hazard
will be more like the lower hazard as time passes. At the aggregate level this will show up as
duration dependence although it may simply be a reflection of different groups having different
(constant) hazard rates.
The fewer significant duration parameters compared to Stevens (1999), suggests that state
dependence for poverty spells is a greater problem in the USA than in Denmark.
Table 5. Exit and re-entry rate parameter estimates, with heterogeneity. ML-estimates
from (9)
Estimate St.error Estimate St.error
Woman -0.1616 0.1029 -0.2761 0.1238
Age: 30-39 years 0.0193 0.1319 -0.2581 0.1338
40-49 years 0.2500 0.1434 -1.0391 0.1537
50-59 years -0.2540 0.1763 -1.3844 0.1539
60+ years -0.0247 0.1807 -2.0255 0.1778
Indicator for being single -0.6235 0.1123 0.3434 0.1427
No of children -0.3508 0.0602 0.4832 0.0798
Education, years, incl. sch. 0.0545 0.0209 -0.1230 0.0225
Annual hours employed/100 0.0674 0.0107 -0.0653 0.0101
Aggregate unemployment rate, % -0.1217 0.0304 0.0604 0.0284
Duration: 1 0.3704 0.1786 -0.0016 0.1211
2 0.2182 0.1630 -0.3645 0.1789
3 -0.0549 0.1610 -0.7401 0.1871
4 -0.0081 0.1096 -0.7937 0.1740
5 0.3748 0.1676 -1.6013 0.2879
6 0.0843 0.2364 -1.0961 0.2530
7 -0.3694 0.3878 -1.4740 0.1600
8 0.0370 0.4011 -0.8609 0.2154
9 -0.6031 0.4716 -1.4257 0.1821
10 -0.8959 0.6007
? 0
? 0.9592 0.2341
? 0
Person type probability P 1 (
? ,
? ,
-2.4322 1.4412
? ) 0.3248 (estimate) 0.0714 (St.err.)
? ) 0.3850 (estimate) 0.0709 (St.err.)
? ,
? ) 0.0001 (estimate) 0.0000 (St.err.)
? ,
? ) 0.2901 (estimate) 0.1246 (St.err.)
Log likelihood -2,142.1
Simulation of years in poverty
Although the signs of estimated coefficients are interpretable, the magnitude is less so. In this
paragraph the coefficients in Table 5 are therefore used to calculate the distribution of years in
poverty by applying the methodology described in the following.
Define ḙ as the estimated exit rate from poverty after
d years of poverty and define rˆ d
as the
estimated re-entry rate into poverty after d years of non-poverty. The following fraction of the
population, who starts a poverty spell, will have 1 year of poverty out of the next 11 years:
P ( d
? 1) ?
1 ? (1 ? rˆ
In the same manner the fraction with poverty in the whole period is calculated as:
P ( d
? 11) ?
(1 ?
ˆ )
e s
Duration between 2 and 10 years of poverty is more difficult to illustrate (six years of poverty is
possible in 252 different ways), but the technique is similar: First, calculate the probability of all
sequences that lead to d years of poverty. Second, sum the probabilities that each lead to d years
of poverty. The data include 11 years, but the first year is with certainty a year in poverty. The
total number of different sequences is thus 1,024 (=2 11-1 ). This simulation approach is different
from Stevens (1999), who simulates the distribution of years in poverty by using estimated
coefficients and random draws from the logistic distribution on observable characteristics for
10,000 individuals beginning a poverty spell. Applying the simulation methodology in the
present paper on Stevens (1999) American exit and re-entry rates actually better replicates the
true American distribution of years in poverty, since the mean square error is reduced from 17.8
to 10.8 and average duration is reduced from 4.4 to 4.2 years, which is closer to the actual figure
of 4 years for the USA, see Table 4.
Table 6. Distribution of years poor, %
1 2 3 4 5 6 7 8 9 10 11 Total (Years)
Representative caseExit rate 0.56 0.53 0.46 0.47 0.56 0.49 0.39 0.54 0.39 0.32
Re-entry rate 0.17 0.13 0.09 0.09 0.04 0.07 0.05 0.04 0.02
Distribution 30.0 19.2 14.2 11.2 8.9 6.2 4.3 2.9 1.7 0.9 0.7 100 3.2
-Only exit rate 56.2 23.0 9.6 5.3 3.3 1.3 0.5 0.4 0.1 0.1 0.2 100 1.9
Heterogeneity Low e, high r 14.2 13.3 12.7 12.3 12.3 10.3 8.7 6.9 4.6 2.6 2.0 100 4.6
Low e, low r 22.4 20.9 18.8 15.0 10.7 6.6 3.4 1.5 0.5 0.1 0.0 100 3.2
High e, low r 36.5 21.4 12.3 9.0 7.9 4.3 2.4 2.4 1.1 0.7 2.0 100 2.9
High e, high r 57.8 23.4 9.7 4.8 2.6 1.0 0.4 0.2 0.1 0.0 0.0 100 1.8
Notes: Simulations are based on the average of explanatory variables, see Table A1 in appendix, and estimated parameters in Table 5. The entries in row
4 represent the distribution of year in poverty, when a single spell approach is used.
High exit rate from poverty (e) means that the person has heterogeneity of type 2, so the logit of exit is increased by 0.9592 (estimate from Table 5)
Low exit rate from poverty (e) means that the person has heterogeneity of type 1, so the logit of exit is unchanged (normalised to zero in Table 5)
High re-entry rate into poverty (r) means that the person has heterogeneity of type 1, so the logit of re -entry is unchanged (normalised to zero in Table 5)
Low re-entry rate into poverty (e) means that the person has heterogeneity of type 2, so the logit of re-entry is reduced by –2.4322 (estimate from Table
As estimated parameters are not a result of linear regression, the parameters must be evaluated at
some values for the explanatory variables. The evaluation point here is the vector of averages for
the different explanatory variables using all person years (see Table A1 in the Appendix). This
representative case is a 34-year-old (starting year average) single woman with 11 years of
education incl. schooling and 1 child living at home. She works 648 hours a year in a labour
market with 9.8% unemployment. Except for age, all variables are held constant through out the
11-year period. The effect of explanatory variables is calculated by changing one variable at a
time in the representative case. The exit and re-entry rates are then used to calculate distribution
of years in poverty and average poverty during the next 11 years.
Starting with the representative case, 63% of persons with the above mentioned characteristics
who enter poverty, only stay there for one, two or three years out of the following 11, see Table
6. 33% have a duration lasting 4 to 8 years, while 3% are severely poor, implying that poverty
lasts at least 9 years out of 11. 0.7% are always poor. This distribution of years in poverty implies
an average of 3.2 years in poverty out of 11 years. The representative case much resembles the
average of the population, see column three in Table 3. The slight underestimation of average
poverty duration is primarily because the actual distribution has a heavier right tail than the
simulated distribution. The distribution depends on exit and re-entry rates, and compared to Table
2, it is clear that the actual distribution has lower exit rates than the simulated distribution and
generally higher re-entry rates than those calculated from Table 5.
The single spell approached has been used in row 4 of Table 6. Using only the exit rates from
poverty, more than half (56%) of the poor would only stay 1 year in poverty as opposed to less
than 1/3 in the multiple spells approach. The distribution of years in poverty implies that on
average a poverty spell lasts for 1.9 years.
The estimated heterogeneity has great implications for the years spent in poverty and therefore
average poverty duration. It is seen that the 32% with the least favourable unobservable
characteristics (low exit rate and high re-entry rate) have on average 4.6 years in poverty, as
opposed to 1.8 years for individuals with favourable unobservable characteristics (high exit rate
and low re-entry rate), see Table 6. Therefore, when the former group is hit by poverty, they stay
there 2½ times longer than the latter group. The intermediate groups (low exit rate, high re-entry
rate and high exit rate, low re-entry rate) have an average poverty duration similar to the
representative person.
The heterogeneity parameters are included in the simulations in the following way. For each
person type (e.g. men, 40-49-years old or 5.7% aggregate unemployment) four distributions of
years in poverty are calculated from the four sets of exit and re-entry probabilities. The final
single distribution for each person type, which is presented in the Tables, is then calculated as a
weighted average of the four different distributions, which reflects the four different
heterogeneity combinations. The weights are P ,
P and
3 P . For instance the representative
case in row 3 of Table 6 is the weighted average of the last four rows.
Table 7. Distribution of years poor, %
1 2 3 4 5 6 7 8 9 10 11 Total
Gender Men 28.8 18.6 14.4 11.8 9.4 6.6 4.5 2.9 1.7 0.8 0.5 100 3.3
Women 30.9 19.5 14.0 10.7 8.5 5.8 4.1 2.8 1.8 1.0 0.9 100 3.2
etween single men and single women. Men and women have slightly different routes to this
almost common average, because women have relatively fewer in the middle of the distribution
and more in the upper and lower tail than men, see Figure 1. Women thus have a little higher
inequality in the distribution of poverty than men.
Figure 1. Distribution of years poor, %
Worst case
Best case
Unem.: 12.4%
Unem.: 5.7%
Unemp.: +1%-p.
Work: +500 h
Work: +100 h
Educ.: +5 year
Educ.: +1 year
3 children
2 children
1 child
No children
60+ years
50-59 years
40-49 years
30-39 years
Under 30 years
0% 20% 40% 60% 80% 100%
1-3 years 4-8 years 9-11 years
Age has a negative impact on poverty duration (Table 7), which is mainly due to significant age
effects on the re-entry rates, while exit rates are unaffected by age. Individuals with a starting age
less than 40 years have an average poverty duration around 3.2-3.5 years, while older individual's
durations are between 2.3-2.8 years. This negative age effect is also found in Stevens (1999). A
likely reason for this pattern is that the young have lower wages and higher unemployment rates.
The children and marital parameters in Table 5 are all highly significant and with predictable
signs. More children or living without a partner thus reduce the exit rate from poverty and
increase the re-entry rate from non-poverty. An extra child in the family increases poverty
duration by about 0.9-1.2 years on average and living alone increases poverty duration by 1.1
years, see Table 7. Owing to non-linearities in the estimation, the impact of children is increased
with the number of children. The presence of children could have adverse effects because they
usually do not earn income, but they are included as a consuming unit. All else equal, the
equivalence scales imply lower income for fami lies with children. Further, the caring and rearing
responsibilities of parents means that employed hours and career prospects could be reduced,
causing lower income.
Schooling and working time also has the expected signs and is highly significant. However, the
effect on average duration is not of great magnitude. 5 years' extra education or 500 hours more
work annually thus reduce the average poverty duration by 0.6-0.8 years. Measured in years the
effect is not great, but it is a reduction of 20-25% compared to the representative person. In
Stevens (1999) higher or further education reduces average poverty duration by 17-20%. An
explanation for the positive effect of education is found in the human capital theory, which
predicts a positive relationship between human capital (number of years of schooling) and hourly
wage rates or the probability of having a job.
The only macroeconomic variable included, the aggregate unemployment rate, has significant
and predictable signs. A tight labour market thus increases the poverty exit rate, because
employment chances are better and people hit by poverty therefore have better prospects of
escaping it. Low unemployment chances likewise reduce the re-entry probability. Thus a 1 %-
point increase in the aggregate unemployment rate increases the average poverty duration from
3.2 to 3.4 years.
The most recent annual unemployment rate for Denmark is 5.7% in 2000 compared to a
maximum of 12.4% (in 1993) when the last recession had the most severe effect on the labour
market. Using these two unemployment rates (assuming 5.7% and then 12.4% unemployment in
all years, e.g. a non-gradual or sudden change is simulated) implies average poverty duration of
2.5 and 3.8 years, or a reduction of about 35%, when the economy moves from high to low
aggregate unemployment. Therefore, over the business cycle, the unemployment rate may indeed
have great effects on time spent in poverty.
Unemployment effects reported here differ to those in Pedersen and Smith (1998), who also on
Danish data, conclude, that exit rates and re-entry rates are rather insensitive to macro economic
cyclical factors. The discrepancy may be due to the inhomogeneous data used in estimation of
hazard rates in Pedersen and Smith, see Paragraph 5.1.
High effects of unemployment over the business cycle suggest that although unemployment
benefits as well as other social benefits are comparatively high, the welfare state does not entirely
protect individuals from poverty in the case of rising aggregate unemployment.
Devicienti (2000) has a number of models in his study, but only for the model containing adults
does he get the same qualitative results regarding the aggregate (local) unemployment rate as in
this study.
To illustrate other possible analysis, a worst and a be st counterfactual is simulated. The best case
is a person with favourable observable as well as unobservable characteristics. It is a 40-year-old
man without children, but with the highest educational level (18 years) and working three times
longer than the average person in a labour market characterized by low aggregate unemployment
(7.9%). The opposite case is a young single mother (starting age 20 years) with three children,
low education (9 years), without work and living in a period with high unemployment (12.4 %).
The best case has an unobserved high exit rate and low re-entry rate, while the worst case has an
unobserved low exit rate and a high re-entry rate.
Individuals in the best case almost all only stay in poverty for one year. Only 5.7% stay another
year and less than ½% stay for 3 years. This implies average durations of 1.1 years. In the worst
case scenario more than half are always poor, once hit by poverty, while practically none of them
stay in poverty for less than 5 years. The average duration for this last group is 10.3 years out of a
maximum of 11 years of poverty.
The average poverty durations mentioned in this Paragraph are almost unaffected when leftcensored
spells included or when unobserved heterogeneity effects are not included, see the
results in Paragraphs A5.3 and A5.4 in the Appendix.
6. Conclusion
Poverty persistence has been modelled and estimated and the estimates have been used to
simulate distribution of years in poverty. This study confirms that the single spell approach is
quite inaccurate and clearly underestimates the total time spent in poverty, because the possibility
of re-entry is not taken into account. The multiple spells approach much more precisely replicates
the actual distributions of years poor.
Simulations show that estimated coefficients have some impact on the distribution of years poor
and thereby on the average total time spent in poverty over a given number of years. In particular,
education and working hours significantly increase exit rates from poverty and decrease re-entry
rates back into poverty, while the presence of children and living without a partner significantly
decrease exit rates and increase re-entry rates. Low unemployment in the economy is also
important in lowering the average duration of poverty. Gender is less important for the
determination of total time spent in poverty.
The hazard rate model with heterogeneity is significantly better than the model where unobserved
heterogeneity is ignored. However, the effects on the distribution of years poor are not
remarkable. The inclusion of left-censored cases like-wise does not greatly alter the results.
Although the duration of poverty is an important dimension of poverty, it is also important to
extend the analysis, to include other dimensions, e.g. the severity of poverty.
Aaberge, R., A. Björklund, M. Jäntti, P.J. Pedersen, N. Smith and T. Wennemo (1997):
"Unemployment Shocks and Income Distribution How Did the Nordic Countries Fare During
their Crises?" Discussion Papers 201, Statistics Norway
Aaberge, R. and I. Melby (1998): " The Sensitivity of Income Inequality to Choice of
Equivalence Scales", Review of Income and Wealth, vol. 44, no. 4
Bishop, J.A., J.P. Formby and B. Zheng (1999): "Distribution Sensitive Measures of Poverty in
the United States", Review of Social Economy, vol. 57, no. 3
Bane, M.J. and D. Ellwood (1986): "Slipping Into and Out of Poverty: The Dynamics of Spells",
Journal of Human Resources, vol. 21, no. 1
Buhmann, B. (1988): "Equivalence Scales, Well-Being, Inequality, and Poverty: Sensitivity
Estimates across Ten Countries Using the Luxembourg Income Study (LIS) Database", Review
of Income and Wealth, vol. 34, no. 2
Burkhauser, R.V., B.A. Butrica and M.C. Daly (1995): "The Syracuse University PSID-GSOEP
Equivalent Data File: A Product of Cross-National Research", All-University Gerontology
Center, Maxwell School of Citizenship and Public Affairs, Syracuse University
Burkhauser (1996), R.V., T.M. Smeeding, J. Merz: "Relative Inequality and Poverty in Germany
and the United States Using Alternative Equivalence Scales", Review of Income and Wealth, vol.
42, no. 4
Coulter, F., F. Cowell and S. Jenkins (1992): "Equivalence scale relativities and the extent of
inequality and poverty", The Economic Journal 102
Devicienti, F. (2000): "Poverty Persistence in Britain: A Multivariate Analysis Using the BHPS,
1991-1997", Institute for Social and Economic Research, University of Essex
Duncan, G. (1983): "The Implications of Changing Family Composition for the Dynamic
Analysis of Family Economic Well-Being", in "Panel Data on Incomes" by A.B. Atkinson,
London School of Economics
Duncan, G. and W. Rodgers (1991): "Has Children's Poverty Become More Persistent?"
American Sociological Review, vol.56, no. 4
Eberwein, C, J. Ham and R. Lalonde (1997): "The Impact of Being Offered and Receiving
Classroom Training on the Employment Histories of Disadvantaged Women: Evidence from
Experimental Data", Review of Economic ", American Sociological Review, vol. 56, no. 4
Danish Economic Council (2001): "Dansk økonomi" (Danish Economy), Autumn 2001
Findlay, J. and R.E. Wright (1996): "Poverty and the Intra-household Distribution of Resources",
Review of Income and Wealth, vol. 42, no. 3
Förster, M.F. (1994): "The Effects of Net Transfers on Low Incomes among Non-elderly
Families", OECD-Economic-Studies, no. 22
Gallie, D. and S. Paugam (2000): "Welfare Regimes and the Experience of Unemployment in
Europe", Oxford University Press, London, UK
Gustafsson, B. (1995): "Assessing Poverty: Some Reflections on the Literature", Journal of
Population Economics, vol. 8, no. 4
Hauser, R. and H. Fabig (1999): "Labor Earnings and Household Income Mobility in Reunified
Germany: A Comparison of Eastern and Western States". Review of Income and Wealth, vol. 45,
no. 3
Heckman, J.J. (1981): "The incidental parameters problem of initial conditions in estimating a
discrete time-discrete data stochastic process" in C.F. Manski and D. McFadden's (eds.)
"Structural Analysis of Discrete Data with Econometric Applications, Cambridge, MIT Press
Hill, M., D. Hill and R. Walker (1998): "Intergenerational dynamics in the USA: poverty
processes in young adulthood", in L. Leisering and R. Walker (eds.): "The Dynamics of Modern
Society – Poverty, policy and welfare", The Policy Press, University of Bristol, UK
Krause, P. (1998): "Low income dynamics in Unified Germany" in L. Leisering and R. Walker
(eds.): "The Dynamics of Modern Society – Poverty, policy and welfare", The Policy Press,
University of Bristol, UK
Lancaster, T. (1990): "The Econometric Analysis of Transition Data", Cambridge University
Press, Cambridge
Meyer, M.D. (1990): "Unemployment Insurance and Unemployment Spells", Econometrica, vol.
58, no. 4
Ministry of Economic Affairs (1993): "Lovmodel" (Law Model), Denmark
Moffitt, R. and M. Rendall (1995): "Cohort Trends in the Lifetime Distribution of Family
Headship in the US, 1968-1985", Demography, vol. 32, no. 4
Nicholson, J.L. (1979): "The assessment of poverty and the information we need" in HMSOs
"Social Security Research: the Definition and Measurement of Poverty", London
Pedersen, P. and N. Smith (1998): "Low Incomes in Denmark. 1980-1995". Centre for Labour
Market and Social Research. Working Paper no. 19
Sen, A. (1976): "Poverty: An ordinal approach to measurement", Econometrica, no. 44
Stevens, A.H. (1994): "The Dynamics of Poverty Spells: Updating Bane and Ellwood",
American Economic Review, vol. 84, no. 2
Stevens, A.H. (1999): "Climbing Out of Poverty, Falling Back In", The Journal of Human
Resources, XXXIV, no. 3
Stewart, M.B. and J.K. Swaffield (1999): "Low Pay Dynamics and Transition Probabilities",
Economica, no. 66
Table A1. Sample statistics over all person years, 1981-1997, 6,072 observations (average
etc. calculated over all years)
Mean St. error Minimum Maximum
Woman 0.544 0.498 0 1
Age 38.813 13.382 18 74
Single 0.601 0.490 0 1
Children 0.543 0.939 0 7
Education, years 11.437 2.574 9 18
Annual work hours/100 6.484 7.113 0 34.96
Aggregate unemployment rate, % 9.768 1.311 7.9 12.4
Fraction in different brackets
Age, years Under 25 0.144
26-45 0.569
46-54 0.125
55-64 0.106
65+ 0.056
Number of children None 0.678
01-feb 0.274
3+ 0.048
Education, years 9 0.348
10 0.121
11 0.011
12 0.327
14 0.075
16 0.061
18 0.056
Annual number of working hours None 0.413
1-500 0.134
501-1,000 0.117
1,001-2,000 0.332
2,000+ 0.005
A5.3. Estimation without unobserved heterogeneity
To detect any bias in estimates when not modelling unobserved heterogeneity estimation was
made without the heterogeneity terms in (9).
Table A8. Exit and re-entry rate parameter estimates, without
heterogeneity. ML-estimates from (9), excluding ? 's
Estimate St.error Estimate St.error
Woman -0.1413 0.0951 -0.2903 0.1176
Age: 30-39 years 0.0341 0.1058 -0.2461 0.1288
40-49 years 0.2473 0.1310 -1.0360 0.1308
50-59 years -0.2155 0.1522 -1.3496 0.2143
60+ years 0.0240 0.1610 -1.9272 0.2650
Indicator for being single -0.5645 0.1091 0.2286 0.1365
No of children -0.3319 0.0548 0.4045 0.0668
Education, years, incl. schooling 0.0471 0.0215 -0.1338 0.0226
Annual hours employed/100 0.0601 0.0105 -0.0599 0.0094
Aggregate unemployment rate, % -0.1181 0.0346 0.0279 0.0299
Duration: 1 1.0093 0.3852 0.2243 0.2171
2 0.7720 0.3925 -0.2058 0.2307
3 0.4207 0.4010 -0.6160 0.2532
4 0.4042 0.4119 -0.7114 0.2679
5 0.6981 0.4132 -1.5673 0.3238
6 0.3530 0.4570 -1.1118 0.2964
7 -0.1501 0.5764 -1.5209 0.2609
8 0.2084 0.4663 -0.9774 0.3154
9 -0.4229 0.8230 -1.6121 0.2912
10 -0.7981 0.6146
Log likelihood -2,150.9
Compared to Table 5, the parameters in Table A8 generally have a lower ratio between estimates
and their standard errors. On a 5% significance level, the parameters of education and duration in
the exit regression, and the parameters of single, aggregate unemployment and duration 2 in the
re-entry regression are significant in Table 5, but not in Table A8.
Based on the two likelihoods in Table 5 and A8, there is a clear rejection of a model reduction
from the one with heterogeneity to the one without heterogeneity. The question is whether this
has any practical significance, for instance for the simulated durations. Because, looking at the
parameters, no major differences are revealed, except for the duration parameters. A simulation
based on the parameters in Table A8, gives the poverty distribution in Table A9.
Table A9. Distribution of years poor, % (without heterogeneity)
1 2 3 4 5 6 7 8 9 10 11 Total (Years)
Representative case 27.3 20.4 15.6 12.0 9.2 6.3 4.1 2.6 1.4 0.7 0.6 100 3.2
Gender Men 25.2 20.0 16.1 12.8 9.9 6.8 4.3 2.6 1.3 0.6 0.5 100 3.3
Women 28.8 20.6 15.1 11.4 8.8 5.9 3.9 2.6 1.4 0.7 0.8 100 3.2
Stevens (1999) also present estimates, where unobserved heterogeneity is ignored, but without
concluding about the differences. Inspecting the results shows that her estimated parameters are
also only little affected by the modelling of unobserved heterogeneity on American data.
A5.4. Estimation including left censored spells (without unobserved heterogeneity)
Until now a person was only included in the sample if the poverty spell started after the start of
the sample. This was to avoid left-censored spells that can bias estimated hazard rates. To see
how left-censored spells would affect the result, estimation is made with left-censored spells
included for the same time period, see Table A10.
Table A10. Poverty estimation with left censored spells (15,180 person years, 1,380 persons)
ML-estimation of (9), without heterogeneity Hazard rates Distribution, %
Exit Re-entry Exit Reentry
Estimate St.error Estimate St.error
Woman -0.080 0.062 -0.223 0.084
Age: 30-39 years -0.212 0.102 -0.289 0.125
40-49 years -0.182 0.107 -1.061 0.153
50-59 years -0.442 0.133 -1.338 0.198
60+ years -0.313 0.126 -1.900 0.200
Indicator for being single -0.551 0.080 0.294 0.103
No. of children -0.326 0.045 0.419 0.063
Education, years, incl. schooling 0.063 0.016 -0.124 0.020
Annual hours employed/100 0.076 0.007 -0.093 0.007
Actual Simu -
Aggregate unemployment rate, % -0.136 0.024 -0.030 0.024
Duration: 1 0.757 0.247 0.711 0.202 0.544 0.194 24.7 26.6
2 0.581 0.252 0.333 0.211 0.500 0.142 18.8 21.0
3 0.468 0.262 -0.044 0.223 0.420 0.078 14.1 16.0
4 0.354 0.269 -0.534 0.245 0.392 0.049 10.5 11.6
5 0.142 0.277 -0.487 0.253 0.343 0.052 8.4 8.4
6 0.936 0.275 -0.704 0.277 0.536 0.042 9.1 6.6
7 -0.236 0.342 -0.874 0.306 0.263 0.036 3.0 4.1
8 -1.044 0.469 -0.483 0.292 0.138 0.052 3.0 2.5
9 -0.436 0.431 -1.129 0.370 0.227 0.028 2.8 1.4
10 -0.498 0.481 0.216 2.0 0.8
11 3.8 0.9
Total, % 100 100
Average duration, years 3.7 3.2
Note: Hazard rates and the implied distribution of years poor is for the representative person in the new sample including left censored spells
(averages over all person years, except age, which is the average age at spell start )
Compared with the estimations and simulations in paragraph 5.3, inclusion of the left-censored
cases has only little impact on the estimated parameters. Many exit parameters are still
insignificant, but the significant re-entry rates are close to the parameters in Table 8. The
simulated distribution deviates somewhat from the new actual distribution. The average duration
is estimated to be 3.2 years, while the new actual duration is 3.7. Compared to the actual
distribution in the case without the left-censored observations (Table 3), the inclusion of leftcensored
spells does not give poorer predictions. The estimated duration of 3.2 years is thus close
to the actual distribution of 3.3 years in Table 3. Effects of variables (not shown) are also close to
the effects presented in Table A9. This insensitivity to inclusion of left censored spells is also
found in Stevens (1999).


text:
Private label hair product manufactuers työt
...built it with wordpress 5 and elementor pro. I have basic knowledge about installing and maintaining the website but need help integrating woocommerce and building simple product catalog. For example this website of my competitor has quite simple catalog for used (brokerage) and new boats: [kirjaudu nähdäksesi URL:n] Also
Ripsaw ev2
Massage Oil Label
private job
PRIVATE PROJECT FOR nishantjain21
Mailchimp Template Private job
Private job for Melissa
database job
Hello, Private [kirjaudu nähdäksesi URL:n] [kirjaudu nähdäksesi URL:n] [kirjaudu nähdäksesi URL:n] [kirjaudu nähdäksesi URL:n] job. Private [kirjaudu nähdäksesi URL:n] [kirjaudu nähdäksesi URL:n] [kirjaudu nähdäksesi URL:n] job.
update recent job
Minulla on edelliseen projektiimme liittyvää jatkuvaa työtä 'IoT product enclosure'
private jobbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbb
private job
Private job.
private job
private job!!!!!!!!!!!!!!!private job!!!!!!!!!!!!!!!private job!!!!!!!!!!!!!!!private job!!!!!!!!!!!!!!!private job!!!!!!!!!!!!!!!
private job....private job....private job....private job....private job....private job....private job....private job....private job....private job....private job....private job....
Private JOB For Marjan
Private job!!!!!! Private job!!!!!! Private job!!!!!! Private job!!!!!! Private job!!!!!!Private job!!!!!!
private job private job private job private job private job private job private job private job private job private job
private jobbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbb private jobbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbb private jobbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbb
private job
Privatr jobssssssss .......................................................................... .........................
...software for this project (either way is ok); and 2) whether you have worked on projects involving [kirjaudu nähdäksesi URL:n] or similar pages in the past. 3) This program should be for private use and not offered to other possible clients Also would like to work with in the future as the ticket seller does change its software from time to time. Program Requirements:
The configurable product can be added from the quick shop, product page but not the category page. Always get "You need to choose options for your item." message.
Need a professional Photographer
Hi! We are conducting market research and testing on our new software release (Chrome Extension). We can provide content and graphic design as needed, just need someone who is creative and knows how to grow pages organically with results and test software. Please put "eez8w" in your bid proposal.
I need you to write some content for a website.
...universities, they also fall in three categories. These are:Government schools Private schoolMadaras Talking about the government institutions first, they are in poor condition due to lack of attention and shortage of funds. Teachers are not given adequate salary. Private schools, on the other hand are doing much better job. There are number of school
I want to re-draw ( 4 ) psd files and converted to illustrator files (vectors files) and ready for final printing. cont...to re-draw ( 4 ) psd files and converted to illustrator files (vectors files) and ready for final printing. contents has Arabic and English text. project for 2 water bottle label and 2 boxes. work should be done within max 48 hours
I need 500 words description with STRONG English. Native writer's only. Need to start now Thanks
...represent it mathematically : The task is marked done if I : 1. Receive a prediction model based on a machine learning algorithm (details of the wanted model will be discussed in private) 2. Represent the model mathematically by equations and explain them in details. [kirjaudu nähdäksesi URL:n] of prediction especially the accuracy of the model(with the plot). 4. A document
Hello, I want my android app (Cordova) to use my ser...priting functions in [kirjaudu nähdäksesi URL:n] and you will also see the same serial interfaces in both the java and cordova plugins, we want the printing from my cordova application (kept private for now) to use the serial printer. it should be simple if you have knowledge of android and cordova. thanks.
I need a web application for client use that integrates with Wowza Servers API. The final product must be similar to [kirjaudu nähdäksesi URL:n] but with a white label option. In short a client would logon and send their stream to the Wowza Ingest Server. Their Dashboard needs to show the incoming stream & bitrate as well as any saved forwarders. The client should
what is the best way you can make the word BARnanaz look This will be used on a banana snack product bar BARnanaz Thank you
Hello, I want my android app (Cordova) to use my ser...priting functions in [kirjaudu nähdäksesi URL:n] and you will also see the same serial interfaces in both the java and cordova plugins, we want the printing from my cordova application (kept private for now) to use the serial printer. it should be simple if you have knowledge of android and cordova. thanks.
We are looking for a chat system to develop/integrate it in our website that it´s build in wordpress. The chat system or messaging it´s a private chat between registered users, I mean 1 user to 1 user: - There are no group chats - Only registered users will be able to launch the chat - User will be able to attach photos - We have two kind of users
Hi Freelancers W...online store. It is a house plan store. Work involves entering pictures and descriptions in both the store portion and search module of the website. It takes around 20 min per product so about 60 to 65 hrs or work. We will provide sucessful freelancer descriptive video and instructions on proper method of input. Thanks for bidding
bottle label 2 versions / colors
Hello, I need for 4 products Visualisation for use it on my webpage, product customisation. For ex: Pallet racking draw but all parts sepeared. Thanks for bidding
I am looking for a private label specifically for little girls jewelry toy. I need a label with a UNICORN. It would be cool for the unicorn to be wearing a little girls necklace. I would also like my LLC name on the label "The Original Life". Lastly, I want the words "Pop Beads" to be on the label somewhere as this is the product we wil...
For a private swiss foundation, I'm looking for someone who's able to add a page on Wikipedia.
I need a website for a bakery product to be sold in USA. Packaging design is already [kirjaudu nähdäksesi URL:n] time is two weeks.
Make the attached logo into a proper SVG Logo. The colors and design of the attached are pretty much what I am looking for. So, easy job.
...Sharepoint (saving files to Sharepoint folder URLs given as an argument). A bigger and useful task would be converting the code from Python 2 to 3. We have the code on a private GitHub project. It is imports [kirjaudu nähdäksesi URL:n] All pretty short and sweet (only a few hundred lines code). It is well commented.
We need a better wolf to be the center of our logo. I...have a basic clip art which we really like the "smiling" aspect of the wolf's face and I have an artists rendering (no copyright- just a sample) which has more details like hair, etc... We need the basic shape of the wolf from the clip art with artistic details added for a more professional look.
We are currently looking for an experienced System Engineer for a lucrative, long-term freelance opportunity in Basel. If you're interested, I'd love the opportunity to talk it over with you in more detail. Please let me know the most suitable time and the best number to reach you on.
Label from manufacturer needs to be rebranded for private label with Titan markings Label file needs to be able to be edited. Product information fields should be easily editable by the our staff so we can change the label specs and name for multiple products. Label Dimensions are 3.5" wide by 4" tall Branding guidelines must be followed ...
I have ongoing projects for my boards and looking for someone who can handle my investments and legal financial banking on a weekly or daily basis Someone who is well trained and well participated in banking and auditing sectors and also should be bold and smart to handle Individually or by a company is not a matter but the work had to go perfect and tension-free.
Locate image (.jpg or .png) for a list of approximately 300 books. Images must be at least 500 pixels in height, must not have any watermark text (e.g. "Copyrighted Material"), and they must be professional in appearance. Ideal images are stock pictures from book publishers. Please avoid amateur looking images of books. You may use Google Books, Amazon, or any other resource so long as r...

subset: commoncrawl


text:
There was a point half way through the day when I couldn't stop giggling. Along with the rest of the tour group, I was standing on a beach on the south east coast of Iceland. We were all very cold and it was snowing. The on-line brochure and accompanying research I'd done before-hand suggested clear … Continue reading Extreme Iceland
Tag: weather
It was quite fine when I woke this morning, and then minutes later we had torrential rain. The rain continued as I made my way to work. Half an hour later, and it was sunny. Actually it was hot in my office, and I could feel the warmth of the sun come through. Later it … Continue reading Weird Weather Friday
I left the house reasonably early today, and didn't get home until about ten-thirty tonight. When I left the house, it was fine and sunny and I was wearing shorts, thongs and a polo-shirt; and when I arrived home, I was still wearing shorts, thongs and a polo-shirt, but Sydney was in the midst of … Continue reading Temperamental Sydney
It's been a really busy week. Well, a really busy several weeks, which explains my lack of posting lately. I'm finding that I'm coming home most nights mentally and physically exhausted and collapsing on the couch. I've also been working on the weekends, and so my Saturday has been pretty much collapse on the couch … Continue reading Stir Crazy in Sydney
After a couple of months of travel planning, the reality of my forthcoming trip to Sweden ramped up a few notches today. Sometime last week I installed a number of "Swedish Apps" on my mobile phone, includng one which lists the 4-day weather forecast for Sweden. And today, for the first time, it actually meant … Continue reading Stockholm Weather


text:
Get a medical capsule immediately!
Rate my bio
srsfunny:Yeets stressfully
Yeets stressfully by KeeganHutch1589
Yeets stressfully via /r/memes http://bit.ly/2IApva6
Yeets stressfully
20+ Animal Memes That Will Definitely Brighten Your Day - Lovely Animals World
I guess I just have a thing for Asian Marxist-Leninist Revolutionaries
Skin safety is important
Me irl
Cartoons ARE pretty WTF if you think about it... #CartoonLogic #WTF #FunnyMemes
K there's this one guy at my school, like, why is he so nice to me? • • • You gotta follow the @frysauces community • • • clean meme memes c...
fakehistory:6th of June 1944 / D-day
6th of June 1944 / D-day
Absolutely beautiful
an icon 🤧
an icon 🤧 by Doncano
an icon 🤧 via /r/memes http://bit.ly/2RfLaZD
Comrades, Henry Scott Tuke 1924.
Two bros chilling at the beach 5 feet apart...
Hey, science side of r/tumblr- does this work?
CHUCK NORRIS first time at the beach.
Comrades, Henry Scott Tuke 1924.
Two bros chilling at the beach 5 feet apar...
Steamy dump IV
He even whipped out the @JAJA
It gets easier each day, because when I feel an urge I just think that the last 5 days weren't for nothing
Oh No
Oh No via /r/funny https://ift.tt/2OkHFel
She Better Not Have The Location On. 😠😠😠 TheyGottaDie
memehumor:I believe that's a blue ring octopus, whose venom can result in death within minutes.
@coupleshabit is the 1 quotes page on instagram!💕💄🌈
purple-raptor:My friend and I made a raptor skeleton out of sand at the beach :


text:
Wedding Cakes in Hyderabad: Check prices and request quotes from all the cake designers in the wedding cakes category. Find everything from bakeries, cake decorating services, wedding cake maker and wedding cake shops in your area.
Baker Street is based in Mehdipatnam, Hyderabad and it offers a variety of cakes and other confectionaries for various events and occasions. It makes all its products with fresh and high quality ingredients, and you can get bespoke creations that totally reflect your demands of the occasion. Be it a... (wedding cake Hyderabad)
Crumble and Melt is a bakery which believes in delivering sweet delights with premium quality tastes and impeccable values. Based in Hyderabad, it popular for its variety of flavours, customised services and products and attentive customer care. It provides baked goods of all varities for various... (wedding cake designs Hyderabad)
Price from ₹1500
Cakes and desserts are meant to add more sweetness to your occasions. If you are looking for an amazing bakery to bake your wedding cakes and desserts then Big Cake Lil Cake is the choice that you should be making. It is a bakery located in the city of Hyderabad and was established in the year 2011.... (engagement cake designs Hyderabad)
Price from ₹500
EBake is a Hyderabad-based bakery that provides an assortment of delicious baked items for weddings and other celebrations. With its experienced team of chefs, they offer a variety of cakes in different flavours and styles that you can choose from to make your wedding memorable. If you have any idea... (engagement cake designs Hyderabad)
Sweet Buds is a wedding cake company that is based in Hyderabad city. Specialising in custom designing they offer freshly baked cakes which are very tempting to eat. Started their venture in 2015 this company has ample options for cakes and desserts. Be it a wedding, cocktail, sangeet night or... (wedding cake designs Hyderabad)
Price from ₹500
If you want to have a cake that adds the sweetest flavours to your event, then look no more. The Cup Cake Factor is here with its delicious flavour to fill your event with a mouthwatering dessert. Wedding cakes should be exclusive and this vendor understands it really well. Located in Hyderabad, The... (wedding cakes Hyderabad)
Price from ₹500
Cakes and desserts are the sources of adding more sweetness to your special occasions. If you are looking for a good bakery to bake your wedding cakes and desserts then Blend and Bakes is the option you must choose. It is a bakery located in Hyderabad and was established in the year 2015. They... (wedding cake Hyderabad)
Price from ₹500
Vineela Yadlapalli Cakes is a bakery based in Hyderabad city and they are capable of providing you with delicious cakes that are not only a treat to the taste buds but are also a pleasure to the visual senses with the gorgeous exterior decor with cream or fondant. The cake is an essential part of... (engagement cake designs Hyderabad)
Price from ₹15000
Cake in a Cup is a premium bakery based in the city of Hyderabad that specialises in designing matchless dessert tables in weddings and other social events. Its professionals are highly experienced and they allow you to customise their products according to your choice, taste and budget. Cake in a... (cake designs Hyderabad)
Cakes and desserts are meant to add more sweetness to your special and grand occasions. If you are searching for a great bakery to bake for your wedding ceremonies, then Nim's Choco Fantasy is the go-to option for you. It is a bakery located in Hyderabad which provides a one-stop solution for all... (wedding cakes Hyderabad)
Price from ₹500
Established in 1997, Eat 'N' Joy Bakers offers customised baked products that you can select to add to your wedding menu. To give your near and dear ones a tasteful delight, the chefs at this company prepares a range of cakes in various flavours and shapes. Using an array of designer toppings, the... (wedding cake Hyderabad)
Price from ₹60000
Cakes and desserts add more sweetness to your happy occasions. If you are in search of a good bakery to make bake your wedding cake then The Chocolate Haven is the choice that you should definitely make. It is an amazing bakery located in the city of Hyderabad and is a one-stop shop for a variety of... (engagement cake designs Hyderabad)
Price from ₹1100


text:
HPE 5130-24G-4SFP+ EI Switch L3 Managed 24 x 10/100/1000 + 4 10 Gigabit Ethernet / 1 SFP+ rack-mountable JG932A The HP 5130 Series is comprised of switches that support static and RIP Layer 3 routing diversified services IPv6 forwarding as well provide four 10-Gigabit (10GbE) extended interfaces. Unique Intelligent Resilient Framework (IRF) technology creates a virtual fabric by managing several one logical device which increases network resilience performance availability while reducing operational complexity.These access can be used at the edge or to connect server clusters in data centers. High simplified management comprehensive security control policies are among key features distinguish this series. The HP 5130 EI Switch Series is comprised of Gigabit Ethernet switches that support static and RIP Layer 3 routing, diversified services, and IPv6 forwarding, as well as provide four 10-Gigabit Ethernet (10GbE) extended interfaces. Unique Intelligent Resilient Framework (IRF) technology creates a virtual fabric by managing several switches as one logical device, which increases network resilience, performance, and availability, while reducing operational complexity.
These switches provide Gigabit Ethernet access and can be used at the edge of a network or to connect server clusters in data centers. High availability, simplified management, and comprehensive security control policies are among the key features that distinguish this series. HPE 5130-24G-4SFP+ EI - switch - 24 ports - Managed - rack-mountable.
Switch - 24 ports - L3 - Managed - stackable. 24 x 10/ 100/ 1000 + 4 x 10 Gigabit Ethernet / 1 Gigabit Ethernet SFP+.
Throughput:96 Mpps Routing/ switching capacity:128 Gbps. IPv4 routing table entries:512 IPv6 routing table entries:256. Static IPv4 routing, static IPv6 routing.
SNMP 1, RMON 1, RMON 2, RMON 3, RMON 9, SNMP 3, SNMP 2c, HTTP, HTTPS, CLI. DHCP support, ARP support, VLAN support, auto-uplink (auto MDI/ MDI-X), IGMP snooping, Weighted Round Robin (WRR) queuing, IPv6 support, sFlow, Rapid Spanning Tree Protocol (RSTP) support, Multiple Spanning Tree Protocol (MSTP) support, Access Control List (ACL) support, Quality of Service (QoS), Jumbo Frames support, MLD snooping, Per-VLAN Spanning Tree Plus (PVST+), Device Link Detection Protocol (DLDP) support, Rapid Ring Protection Protocol (RRPP) support, Endpoint Admission Defense (EAD), STP Root Guard, LLDP support, DHCP relay, Port Security, dynamic ARP protection, DHCP protection, Strict Priority Queuing (SPQ), port isolation, tagged VLAN, Generic Attribute Registration Protocol (GARP), Intelligent Resilient Framework Technology (IRF). IEEE 802.3, IEEE 802.3u, IEEE 802.3i, IEEE 802.3z, IEEE 802.1D, IEEE 802.1Q, IEEE 802.3ab, IEEE 802.1p, IEEE 802.3x, IEEE 802.3ad (LACP), IEEE 802.1w, IEEE 802.1x, IEEE 802.3ae, IEEE 802.1s, IEEE 802.1ad, IEEE 802.3ah, IEEE 802.1ab (LLDP). 44 cm x 16 cm x 4.36 cm.
RADIUS, TACACS+, Secure Shell v. 24 x 1000Base-T - RJ-45 4 x Gigabit / 10Gbit LAN - SFP+ 1 x console - RJ-45 - management. FCC Class A certified, CISPR 22 Class A, CISPR 24, NOM, EN55024, EMC, RoHS, FCC CFR47 Part 15, UL 60950-1, IEC 60950-1, EN 60950-1, WEEE, ANATEL, FDA, EN 60825-1, EN 61000-4-29, CAN/ CSA C22.2 No. 60950-1, ANSI C63.4-2009, VCCI V-3 Class A ITE, EN 61000-3-3:2008, VCCI V-4, EN 61000-3-2:2006+A1:2009+A2:2009, EN 300386, EN 61000-4-4:2012, EN 61000-4-5:2006, EN 61000-4-6:2009, EN 61000-4-11:2004, EN 300 386 V1.6.1, EN55022:2010 Class A, IEC 61000-4-3:2006.
The item "HPE 5130-24G-4SFP+ EI Switch L3 Managed 24 x 10/100/1000 + 4 10 Gigabit Ethernet" is in sale since Sunday, August 14, 2016. This item is in the category "Computers/Tablets & Networking\Enterprise Networking, Servers\Switches & Hubs\Network Switches".The seller is "zippytom_store" and is located in London. This item can be shipped to United Kingdom.


text:
Living Room living room decorations Kitchen Interior Design Sitting Room Design Living Room Styles Drawing Room Decoration
1. Use lighter shades of green, blue and yellow for your walls. These lighter colors or pastels help open up the room and give it a more airy feel. If you want a cozier feel to your living room, use darker shades of red, blue and brown.
Want to create the right impression on your guests? Want your neighbors to know about your eclectic taste? Well, you need undertake the expenditure of painting the entire home. You can customize the living room, make it unique and use it as a canvas to showcase your vibrant style and personality.
new living room designbeautiful living roomsredesign living room ideassofa futonsdecorationsmall living room designsliving room interiorliving room design ideascube ottomanliving room table ideashome decor living roominterior design stylesfront room ideasledge shelfsofainterior design photosliving room picture ideasliving room furniture design ideas
Brighter Shades Make a Space Look Bigger. If you have a large living room, then darker colors might meet your needs. Or else, a lighter shade of paint is better. Eyes are usually attracted to the darker areas of a room, therefore darker colored walls can push your line of vision downward. Consequently, you will feel like the partitions tend to be closer to you than they really are. On the other hand, soft colored walls force your eyes to look up, and the result is a more open and expansive perspective. If you don't have an excessively big live able space or you are making the effort to decrease the feel of the size of the living room, you will want to use brighter shades connected with color.
One of the most important steps to designing your space is deciding on a color palette. Color has the power to shape your mood, so it's important that you choose a palette that's in line with the way you want people to feel when they enter the space. If you want the room to exude serenity and calm, then some cool neutrals are your best bet. If you want more energy in your living room, then you can go with some bold or bright colors. The rest of your design ideas will revolve around your color palette, so choose wisely.
Ultimately, your living room is yours to do with as you choose. If you love Asian inspired elements but also want to display a giant wall portrait of your dog, that's your choice. If you want a Mediterranean style but can't resist making an Andy Warhol print the centerpiece of the room, then you should do it. Your living room should reflect you, and if you have a few quirky interests, then it's only right that your living room should reflect those quirks as well. At the end of the day, living room design ideas are only suggestions, and your preferences should ultimately be the bottom line.
Conditions of Use Privacy Notice Copyright Cookie Policy 2019, Henryfinn.


text:
Our 2019 accommodation listings offer a large selection of 2 holiday lettings near Palestinian Heritage Center. From 2 Flats to 2 Studios, find the best place to stay with your family and friends to discover Palestinian Heritage Center area.
Whether you are travelling with your family or your friends, here are the areas with the largest selection of holiday accommodations for a long holiday or just a weekend break near Palestinian Heritage Center:
For other neighbourhoods, please use our search bar to access the selection of holiday accommodations available.
Yes, of course. HomeAway has 2 Flats near Palestinian Heritage Center. Our other popular types of holiday rentals near Palestinian Heritage Center include:
Yes, you can select your preferred holiday accommodation with internet/wifi among our 2 holiday rentals with internet/wifi available near Palestinian Heritage Center. Please use our search bar to access the selection of self catering accommodations available.
Yes, HomeAway offers a selection of 2 holiday homes to book directly online and 1 with instant booking available near Palestinian Heritage Center. Don't wait, have a look at our self catering accommodations via our search bar and be ready for your next trip near Palestinian Heritage Center!


text:
Wheelchair Ramp Builders in Austin, TX
Prescreened Wheelchair Ramp Builders in Austin, TX
Handyman Connection Of Lakeway
Areas of Expertise
- Doors & Windows
Featured Review
"Company/Handyman was timely, great customer service, very professional. "
Best Austin Handyman and Remodeling
Areas of Expertise
- Handyman
- Kitchen Remodel
- Bathroom Remodel
- Decks, Patios, Pergolas
Featured Review
"They do a great job!"
Low Cost Renovations, LLC
Areas of Expertise
- Bathroom Remodel
- Kitchen Remodel
- Floor Install
- Deck Install or Repair
- Patio Install or Repair
Featured Review
"I wanted to do a kitchen and bathroom remodel to raise my home value before I listed my home. They did an amazing job, and I paid way less than I expected. I sold my house for nearly 50k more than what my realtor initially thought we would list it for. This was such a great investment! Thank you!!"
Austins Power Painting
Areas of Expertise
- Powerwashing
- Painting
- Staining
- Murals
Featured Review
"Great experience! Great value! Great customer service!"
Nature Calling Home Services
Areas of Expertise
- Landscaping Installation and Design
Featured Review
"Our yard was pretty out of control with tall weeds in the front and back. Nature Calling Home Services did a fantastic job! He edged the driveway and sidewalk which was something we haven't done ourselves in years. He also suggested seeding the front yard with Bermuda grass seed in the spring, and we are taking him up on that suggestion. I will definitely continue using this company."
Sky-Lan Services
Newly Screened & Approved
Call for References
Areas of Expertise
- Remodeling
- Basements
- Bathrooms
- Kitchens
- Exterior
Texas Deck Kings
Areas of Expertise
- Decks
- Patio Covers
- Pergolas
- Small Remodels
- Screen Porch Enclosures
Featured Review
"From beginning to end Texas Deck Kings were very professional. Clint and his guys promised perfection and they delivered. The price was by far...BY FAR...lower than other places and they finished on time. If you are getting quotes I would highly recommend getting one from Texas Deck Kings. "
Service Network
Areas of Expertise
- Electrical repair
- Electrical Wiring
- Exterior Building Lighting
- Electrical switches, outlets, and fixtures
- Ceiling fans
Featured Review
"Quality work and prompt service. Highly recommended. "
All Surface Rehab & Renovations
Areas of Expertise
- Handyman
- Painting
- Flooring
- Kitchen & Bath
- Additions
Featured Review
"Fast and on time and quality work. "
Cost to Build or Replace Wheelchair Ramps in Austin
Unscreened Disability Services in Austin, Texas
2505 Zennor Court
Cedar Park, TX 78613
P.O. Box 817
Manchaca, TX 78652
123 Tori Drive
Buda, TX 78610
7310 Sherwood Rd.
Austin, TX 78745
2600 Sherwood Lane
Austin, TX 78704
Things to Consider Before You Build or Replace Wheelchair Ramps in Austin, Texas:
- Where do you need a ramp?
- Why do you need a ramp?
- Of what material do you want the ramp made?
Ideas & Inspiration from Austin Disability Services
Recent Job Requests for Build or Replace Wheelchair Ramps Contractors in Austin, Texas:


text:
News Ticker
- Spotify
- World Of Pop
Other Entertainment Zone
1 topic in this forum
- 1 reply
- 45 views
We have placed cookies on your device to help make this website better. You can adjust your cookie settings, otherwise we'll assume you're okay to continue. Terms of Use Privacy Policy Guidelines


text:
Pulmonologists in Galindo, Austin, TX
Need to make a pulmonologist appointment this week? Use Zocdoc to find pulmonologists in Galindo, Austin who take your insurance. It's simple, secure and free.
Jesus Naranjo,
Dr. Naranjo took his time attending me, he was a very good listener and had genuine interest in me and my wellbeing. He's very personable and caring. This also applies to his staff and nurse - a very positive experience. I'm glad I chose Dr. Naranjo as my primary care physician.
Carlos Licon,
First visit trying to get a P C P for the time I will be working here. The doctortook time to get to know my concerns and started to work on them.
Find doctors and make appointments online
Managing your healthcare is easier than ever before with Zocdoc. Just search for a doctor in your insurance network, see available times, and book an appointment on the spot! You can read real doctor reviews from other patients, see the doctor's background and education, view photos of the office, and more. It's simple, secure, and free!
Find Doctors
- Galindo Cardiologists
- Galindo Dentists
- Galindo Dermatologists
- Galindo Gastroenterologists
- Galindo Ob-gyns
- Galindo Ophthalmologists
- Galindo Orthopedic Surgeons
- Galindo Pediatricians
- Galindo Podiatrists
- Galindo Psychiatrists
- More Specialties
- Allergic Bronchopulmonary Aspergillosis
- Alpha 1-Antitrypsin Deficiency
- Arterial Blood Gas Sampling
- Aspergillosis
- Asthma
- Bronchial Stenosis
- Bronchiectasis
- Pulmonology Consultation
- Pulmonology Follow Up
- Sleep Problems


text:
It's one of the painful things most women go through in their lifetime. In fact, the National Institute of Diabetes and Digestive and Kidney Diseases reports that 40-60% of women will suffer from it at least once in their lifetime. [1]
Urinary Tract Infection, commonly known as UTI, is "an infection that affects any part of the urinary tract, including the kidneys, ureters, bladder or urethra." [2, 3]
While the infection can be brought about by fungi and viruses, most of the time UTI is caused by bacteria from the bowel. These are known as the Escherichia coli and Staphylococcus saprophyticus, which are present in 80% of cases. [4]
UTI is such a common occurrence that it's the second most prevalent infection affecting around 8 million people every year. [5]
While it can practically happen to anyone, women are usually affected by it.
Why are women more prone to it, you ask?
Simple - women have a shorter urethra. Because of this, bacteria from the intimate area can easily enter the bladder and urinary tract.
On the other hand, cases among men are due to an enlarged prostate that holds up urine flow. This is another cause for bacteria accumulating in the urinary tract.
There are various reasons why a person can contract UTI. The following are common causes and risk factors for getting it: [6]
If you experience any of the following, odds are you may be suffering from UTI [8,9]:
According to Mayo Clinic, antibiotics are the first line of treatment for UTI. [10] How long the treatment and the specific drugs to take all depend on the severity of the infection.
One way of getting rid of bacteria, viruses or fungi in the urinary tract? Keep peeing. It's a surefire way of flushing them all out.
And drinking plenty of water helps you pee more.
Don't hold your pee. It may be painful, but it has to be done. Keeping it in will only multiply the bacteria in the urinary tract.
This fruit is your best bet when it comes to treating UTI. Cranberries contain ingredients that get rid of bacteria and take them off the urinary walls. Head over to the grocery store and get some cranberry juice, supplements or dried cranberry snacks.
Complement your cranberry intake with probiotics, which are known to help with digestion as well as UTI treatment and prevention. Probiotics also have good bacteria called Lactobacillus, which can replace the bad ones.
Steer clear of this pesky infection by remembering the 3H's: [6]
Comments will be approved before showing up.
If you always find yourself shedding a few strands of hair in bed or after shower, then there's no cause for panic. Unless you're losing more than 50-100 strands of hair or notice that they're not growing back at all, you're just going through what most women do. But if you think you're losing way more than it should, this article will tell you if you're going bald before it's too late.
Exercise can promote better quality sleep, either by helping people suffering from acute to chronic insomnia fall asleep faster or sleep longer. (Or better yet, both!)
But, does it actually matter what kind of exercise you perform?
Scientific evidence says that vigorous and high-intensity exercise leads to better quality sleep and generally positive mood. [1]
So what are the various types of exercise promoting the best sleep, i.e. most restorative and uninterrupted)? Keep reading!


text:
Hire Latin & Salsa Band in Hounslow
Browse Latin & Salsa Bands
Recent review: I hired Xavier and his colleagues for a work party and found them to be friendly, communicative and, most importantly, superb musicians. Despite a challenging journey down to the south coast, the band added extra flair to our Christmas event and everyone enjoyed it immensely. If you want to do somet
Recent review: """As a manger of a popular London bar I've worked with numerous musicians and was incredibly impressed with the professionalism shown by Sunny Steel Band when we booked them after an act pulled out last minute. My customers enjoyed every minute, and Sunny Steel bought a bit of sunshine to London. I
Recent review: Hi Marcella, Everyone loved the music! It was great and our party wouldn't have been complete without you. Thanks again and hopefully see you again some time soon. Best Wishes Angela
Recent review: We went to see Mariachi Las Adelitas in Hastings after watching one Youtube video and they blew me (and everyone that saw them) away!! We followed them to three venues (in favour of other bands we'd gone to see) as the experience was too good to miss out on. The costumes, the charming introductions
Recent review: "The Mexican Way were fantastic, great communication beforehand and awesome on the night. We went for the full Mexican 'Day of the Dead' theme fancy dress and Mexican meal to start, and the band really topped it all off and made it so different and memorable. Everyone loved the night and commented o
Recent review: Mariachi Margarita were fantastic at our party. They brought exactly the musical blend we had requested and played the kind of traditional Mexican tunes we wanted. They were charming people and the standard of music was terrific. Thank you, we would welcome you back another time. JP
Recent review: @Rio Brass - You were amazing! Thank you for making mine and Simon's wedding day exactly how we had hoped- if you are thinking about booking these guys, make sure you do- they are great, spread the word!!!
Recent review: We had the pleasure of meeting DeAnna and Ingrid in January where they performed for us in our primary school. We celebrated our new topic 'Hola Mexico!' with them. They were great fun and informed the children about their marvelous Mariachi music. A lovely pair of performers and pleasure to meet. I
About: With a flair for performance, this lively Latin band has an engaging energy combined with a vast experience of performing on the London music scene as well as touring the UK and abroad. Their exceptional musicianship, rhythmic drive and colourful Latin style of music - from Salsa to Samba, Latin po
Recent review: Combo Yanze was great. They added great value to our summer party. We even had people outside the gates asking for their business cards!
Recent review: We had the absolute pleasure of having Femme Fusion at a military summer ball. The band were hired to play a two 45 minute sets to a crowd of 150 people. The theme of the ball was Day of the Dead and the band were very accommodating playing music that absolutely set the atmosphere. From an organizer
About: Established in 2013, the Deco Ensemble has been described as an 'exceptional' ensemble 'of the highest calibre', with a 'strong and highly individual voice'.Their adventurous programming and virtuoso performances display extraordinary breadth and creativity. They perform an eclectic and colourful co
Recent review: We cannot recommend David more highly. He played beautifully for our wedding ceremony and drinks reception. He played a wonderful set. The moment I entered the room with my father was made all the more magical with David's own composition. Stunning.
About: De Fuego is a sensational award-winning Spanish guitar duo playing energetic instrumental flamenco and rumba-based music, performing both original music and covers for your special event. If you are looking for something passionate and unique for your special wedding reception, birthday party or fu
Recent review: "Melange were absolutely fantastic! They were so friendly, smiley and gave off a great vibe when playing. The standard and range of music was perfect, there was a great progression of styles and tempo, with our guests enjoying sitting and listening as well as dancing. There were smiling faces everyw
About: Tropicalia is a London based Multi-Award winning company widely recognised as one of the best Latin Brazilian entertainment Group in the UK and Internationally. We have flawlessly entertained audiences throughout the UK, Europe, Middle-East, Brazil and Africa creating seamless and memorable outs
Recent review: Hey Javier just want to say a big thank you for the amazing performance at our wedding on Sunday. Each and everyone we spoke to had no words to express how great it was, how much they loved the music and you guys. Thank you for your flexibility with the set. I know we made you change the timings to
About: Are you looking for an outstanding latin jazz band for your event or private function? The London Latin Collective comprises of musicians from Spain, Brazil and the U.K. that crossed paths on their music ventures in the vibrant city of London. The band will bring you the best mix of Latin music
About: Habanera – London based Latin Ensemble for pubs, clubs, parties, events, festivals and private functions! A wonderfully mixed line up, with experienced and dedicated musicians from around the world performing a range of traditional and contemporary latin arrangements. The large group, featuring a po
About: Saudade Bossa is a music duo project composed of Maria Croft and Mario Correia. The two have met during their Jazz studies at the Middlesex University in London, after which they have established a music relationship in the form of a versatile, Jazz and Bossa Nova-influenced duo, giving Brazilian so