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Glyn Wittwer (email: email@example.com) is a Senior Research Fellow, Centre of Policy Studies, 11th floor Menzies Building, Clayton campus, Monash University, VIC., Australia. Marnie Griffith is a Research Fellow, Centre of Policy Studies, 11th floor Menzies Building, Clayton campus, Monash University, VIC 3800, Australia.
Modelling drought and recovery in the southern Murray-Darling basin*
Version of Record online: 13 JUN 2011
DOI: 10.1111/j.1467-8489.2011.00541.x
© 2011 The Authors. AJARE © 2011 Australian Agricultural and Resource Economics Society Inc. and Blackwell Publishing Asia Pty Ltd
Australian Journal of Agricultural and Resource Economics
Volume 55, Issue 3, pages 342–359, July 2011
Additional Information
How to Cite
Wittwer, G. and Griffith, M. (2011), Modelling drought and recovery in the southern Murray-Darling basin. Australian Journal of Agricultural and Resource Economics, 55: 342–359. doi: 10.1111/j.1467-8489.2011.00541.x
- †
The authors thank the Australian Research Council for funding under project DP0986783.
Publication History
- Issue online: 3 JUL 2011
- Version of Record online: 13 JUN 2011
- Abstract
- Article
- References
- Cited By
- CGE modelling;
- drought
- Top of page
- Abstract
- 1. Introduction
- 2. Enhancing the representation of irrigation in TERM
- 3. Drought in south-eastern Australia from 2006–07 to 2008–09
- 4. Conclusions
- References
The prolonged drought from 2006–07 to 2008–09 in south-eastern Australia presented severe difficulties for dry-land and irrigation farmers in the southern Murray-Darling basin. A dynamic multi-regional computable general equilibrium model (TERM-H2O) is used to estimate the economy-wide small region impacts during and after drought. Drought reduces real GDP in some small regions by up to 20 per cent. Irrigation water trading and farm factor movements alleviate losses. The drought results in an estimated 6000 jobs being lost across the southern basin. Depressed farm investment during drought results in farm capital not returning to baseline levels after drought. Consequently, job numbers in 2017–18 remain 1500 below forecast in the southern basin.
1. Introduction
- Top of page
- Abstract
- 1. Introduction
- 2. Enhancing the representation of irrigation in TERM
- 3. Drought in south-eastern Australia from 2006–07 to 2008–09
- 4. Conclusions
- References
Australia has one of the most variable rainfall climates in the world. Drought can have devastating impacts on agriculture, including dramatic plunges in crop production, loss of livestock and other farm capital and deterioration in the natural resource base. Australia has traditionally afforded its farmers a great deal of drought support. From the early 1980s, however, this free-flowing support came under attack as unnecessary and distorting (see for example, Freebairn 1983). Drought was removed from the natural disasters list and from 1992 has been covered instead by the National Drought Policy. The National Drought Policy has three aims as follows: to encourage farmers to manage their own risks; to look after the natural resource base; and to encourage a quick recovery (O'Meagher et al. 1998).
The aim of this paper is to analyse the regional economic impacts of a prolonged period of recurrent droughts using TERM-H2O, a dynamic computable general equilibrium (CGE) successor to the bottom up, comparative static TERM (The Enormous Regional Model). We concentrate on the regions of the southern Murray-Darling basin (SMDB). One issue concerns the dynamics of drought and drought recovery. In particular, we focus on the implications of drought for regional investment and capital. Another issue is the broader regional economic and employment implications of drought. TERM-H2O models the interaction between irrigation and dry-land agriculture in times of drought, allowing re-allocation of resources across these two activities. Finally, modelling of the impacts of drought provides a benchmark for analysing the impacts of the Australian Government's water 'buyback' policy.
Some analysts and lobbyists have asserted that planned reductions in water used by irrigators in the Murray-Darling basin are similar to the effects of drought (Rizza 2010). Regional impacts generated by various models including TERM-H2O (Dixon et al. 2010) and an ABARE model (ABARE–BRS 2010) have been dismissed as understating the probable employment impacts of reducing allocations, most notably by Murray-Darling Basin Authority board members (Akerman 2010). It would appear that water buybacks, which started during drought, were blamed for job losses that actually arose from drought. Therefore, there is some value in modelling the impacts of drought and estimated impacts on basin employment.
Drought is hard to model, as it entails substantial inward supply shifts for farm sectors. Large change simulations are a challenge for modellers. Linear programming models are likely to reach unrealistic corner solutions with relatively modest supply shifts. Computable general equilibrium models that include CES functional forms will perform better, but most still struggle in large change cases. Consequently, studies on CGE modelling of drought are rare: the only previous studies of which we are aware are Sherony et al. (1991), Horridge et al. (2005) using a version of TERM without water accounts and Pauw et al. (2010). To depict the impacts of a drought as severe as that in southern Australia from 2006–07 to 2008–09 is an extreme test of a multi-regional CGE model. This paper outlines various theoretical modifications undertaken to improve the modelling of drought in a CGE framework and then applies the model to the period from 2005–06 to 2017–18. In particular, we apply a theory of excess capacity to downstream processing sectors.
Results are explained by starting with naïve calculations and outlining how the theory of the model moves simulated results away from these calculations. In addition, the approach provides some estimate as to the impact of prolonged drought on structural change in predominantly rural regions of south-eastern Australia.
1.1. The prolonged drought of 2006–07 to 2008–09
South-eastern Australia endured recurrent droughts after that of 2002–03. From 2003–04 to 2005–06, there was a partial recovery to near-average rainfall in SMDB. Then, the alpine regions of Victoria and New South Wales, which are the source of the Murray River, suffered record rainfall deficits in the period from 2006–07 to 2008–09.1 This resulted in recurrent reductions in water allocations throughout the SMDB. The Goulburn–Murray water authority's allocations illustrate the severity of the first decade of the new millennium: it formerly aimed at providing 100 per cent allocations in 97 years of 100 for the Goulburn system (although the authority removed this aim from its website early in 2010), but has failed to do so in five of eight irrigation seasons starting with 2002–03.
The CGE approach enables us to keep in context the contribution of agriculture to ostensibly rural economies. As agriculture's contribution to the national economy has shrunk, so too has its contribution to regional Australia's economies. For example, our estimates of regional GDP shares indicate that the SMDB's contribution from agriculture in 2005–06 was less than 13 per cent (Table 2, row (5)), little more than the national share in 1962–63 when Australia's population was half of its present total (Maddock and McLean 1987). It follows that although drought still depresses regional economies, the potential impacts are not as large as they might have been had the pattern of drought in the first decade of the new millennium occurred several decades ago. That is, rural economies have also diversified over time, with an increasing share of income being accounted for by service sectors.
|Water allocations and productivity levels (100 = average)
|(1) Dry-land productivity*
|(2) Water†
|Contributions to GDP in 2005–06 base (%)
|(3) Dry land
|(4) Irrigation
|(5) Total
|Naïve estimates of contributions to GDP (%)
|(6) Dry land
|(7) Irrigation
|(8) Total
|Modelled contributions by broad sector
|(9) Dry land
|(10) Irrigation
|(11) Food
|(12) Rest
|(13) Net Water
|(15) Net water sold (GL)
2. Enhancing the representation of irrigation in TERM
- Top of page
- Abstract
- 1. Introduction
- 2. Enhancing the representation of irrigation in TERM
- 3. Drought in south-eastern Australia from 2006–07 to 2008–09
- 4. Conclusions
- References
The first application of the original TERM was to the Australian drought of 2002–03 (Horridge et al. 2005). The original model underestimated the observed change in the composition of farm output. The model did not include water accounts, did not distinguish between dry-land and irrigation technologies and therefore did not capture factor mobility between dry-land and irrigation activities. Despite its limitations, the model estimated state-wide macro-impacts reasonably well (Horridge et al. 2005, Table 4).
Incremental enhancements to TERM started with the inclusion of water accounts (Wittwer 2003). The database of a typical CGE model is based on an input–output structure designated in values. Irrigation water can vary greatly in price between users and years. It is necessary to include volumetric accounts so as to capture differences in water usage per dollar of output between different agricultural outputs. Yet, early applications of this version of TERM did not closely track observed changes in water usage between farm activities in response to changes in water availability. For example, using a version of TERM with water accounts, Young et al. (2006) modelled relatively modest declines in rice output in response to worsening water scarcity. This did not tally with available evidence. Water usage in rice production is highly responsive to changes in water scarcity: total water usage in the Murray-Darling basin dropped by 29 per cent from 2001–02 to 2002–03; yet, usage for rice production in the region dropped by 70 per cent (Table 1). Following the drought of 2002–03, there has only been one year, 2005–06, in which water usage in rice production has reached half of what it was in the years prior to 2002–03.
|Livestock pasture
|Cereals (excl. rice)
|Grapes and fruit
|Other agriculture
|Total agriculture
Dixon et al. (2010) modified TERM on the supply side to reflect the mobility of irrigation water between competing uses. TERM-H2O, the revised model, includes the following:
- •a split in most farm sectors between irrigated and dry-land technologies;
- •three types of farm land, irrigated land, irrigable land,2 and dry land;
- •owner/operator inputs; and
- •specific capital for livestock sectors and for tree and vine crops.
When water availability changes within TERM-H2O, farm factors such as irrigable land, farm capital and owner/operator inputs may move between irrigation and dry-land technologies, or between different irrigation sectors and different dry-land sectors. Specific capital is immobile between sectors, reflecting the relative inflexibility of perennial cropping. The main impacts of these theoretical modifications are to widen differences in the responsiveness of different activities to changes in water availability while increasing farm factor mobility. This was a first step in undertaking large change simulations.
The next step in modelling irrigation sectors and regions in TERM-H2O was to move from a representation at the statistical division level to the statistical sub-division (SSD) level. In the context of irrigation, the finer level of representation aligns more closely with catchment regions. This causes further modelling difficulties. The statistical division level tends to include regions dominated in economic structure by large towns. This makes these regions more service intensive and less agriculture intensive than is the case for rural regions at the SSD level.3 In addition, while at the statistical division level, farm output price rises are moderated by the impact on production costs of downstream processing sectors, at the SSD level, not all regions contain substantial downstream processing sectors. Therefore, the higher concentration of farm activity may result in farm output prices making a larger contribution to terms-of-trade impacts in the smaller regions without being offset significantly by increased costs to downstream users in the same region. Consequently, the model without further modifications may predict unrealistically large terms-of-trade gains in rural regions.
The consumption function in TERM links nominal consumption to disposable income. Terms-of-trade gains affect the price of regional exports (inter-regional plus international), which are included in GDP but not consumption. Regional imports are included in household consumption but not GDP. Therefore, an increase in price of regional exports relative to regional imports (a terms-of-trade gain) raises the ratio of regional real consumption to real GDP. There is a danger that we may model perverse real consumption gains in small regions in times of drought. Rectifying this requires a further theoretical modification.
2.1. Why not make demands for farm products more elastic?
Pen-and-paper models often use the small country assumption in which demands are elastic. This simplifies the impacts of inward supply shifts by guaranteeing that revenues fall as output decreases. But it can also lead to quite unrealistic results. For example, if Australia's farm supply curves move inwards due to drought, and if demands are highly elastic, would not imports substantially or entirely replace domestic supplies? In practice, there is a degree of substitution towards food imports during drought, but for most commodities there is no evidence of a complete switch to imports. Armington (1969, 1970) helped modellers move towards more realistic results (i.e., away from flip-flop solutions) by introducing the assumption of imperfect import substitutability.
More generally, food products follow Engel's law with income elasticities below one. Usual functional forms for household demands in CGE models (Stone-Geary or constant difference of elasticities forms, suitable for broad aggregations of commodities where specific substitutability is not an issue) result in household demand elasticities for food around −0.5 or even smaller. TERM-H2O has export demand elasticities for most commodities other than wool of −4.4 The higher the share of domestic consumption of Australia's agricultural production, the more likely are outputs to have relatively low total share-weighted demand elasticities.
A CGE database includes the details of sales for each farm commodity in a given year to downstream processors, households and exports, plus the value of sales of competing imports to each user. The database weights and various model parameters determine the total elasticity of demand for each farm output. Although much of Australia's agriculture is export oriented, drought-induced inward supply shifts reduce export supplies and thereby lower the total elasticity of demand for farm commodities by increasing the domestic share of total sales. Moreover, drought also increases demand for grains and hay as livestock feed, which pushes up local prices. Freight costs limit the extent to which farmers can purchase feed from distant sources. Imposing more elastic total demands on the model through higher import substitution parameters, higher export demand elasticities and higher expenditure elasticities (the latter in violation of Engel's law) may lead to flip-flop solutions and move us further away from realism.
2.2. The need to model excess capacity in downstream sectors
To find a way of depicting an extreme drought in a CGE model, we consider the impact of drought on downstream sectors. The ability of the downstream manufacturers to cope with lower supplies of inputs depends on a number of factors.
For example, while drought since 2006–07 has put dairy processors based in northern Victoria/southern New South Wales under financial pressure that led to cost cutting via such measures as retrenchments, there has been no substantial rationalisation of capacity to date. A number of factors have contributed to this. First, milk is produced Australia-wide, and processors have the option, although expensive, of transporting milk from non-drought-affected regions. For example, seasonal conditions were relatively favourable in northern New South Wales in 2007 and 2008, resulting in milk being transported south. As a means of reducing industry-wide transport costs, milk swaps between companies (where milk contracted to a given company is supplied instead to the nearest processor and swapped for milk elsewhere) have become commonplace. In addition, the changing feed-base away from irrigated pastures has lead to a flatter pattern of milk production through the year, favourable to the production of the high-valued cheese relative to milk powder. This flexibility in output mix has also helped maintain processor margins in the region.
Other industries do not have as many options. Whereas milk production out of the SMDB has fallen in the order of one-third since its peak in 2001–02, rice output has fallen by more than 90 per cent, with no potential to prop up capacity utilisation by transporting in raw product from elsewhere. The Deniliquin rice mill, previously the biggest rice mill in the southern hemisphere, closed in 2008. In November 2010, Sunrice (2010) announced that the mill would re-open in the coming months. With the return of average or above average rainfall and a restoration of irrigation water allocations, water has once again become cheap enough to enable significant levels of rice production.
A standard CGE model does not capture a reduction in capacity utilisation in downstream processing sectors in response to drought, instead solving for large inward farm supply shifts with consequent implausibly large farm output prices. Far from modelling a drought-induced regional recession, there is a danger that spurious terms-of-trade gains will dominate the scenario. This is not to say that farm output prices do not increase in response to drought. Rather, such price hikes tend to be small relative to output declines. Drought usually is a time of rural hardship, not of regional windfall gains.
In initial attempts to analyse the impact of the global financial crisis on the US economy, Dixon and Rimmer (2010) could not ascribe large inward macrodemand shifts to their model without a consequent large real depreciation. There were no observed large real exchange rate adjustments to the US economy during the crisis. In response, the authors devised a mechanism to mimic excess capacity, motivated by the Keynesian theory of multiple equilibria, in which price adjustments alone will not dig an economy out of recession. The implementation of excess capacity solved the problem. By analogy, as the excess capacity mechanism choked off an unrealistic real depreciation in Dixon and Rimmer (2010), we felt that it could also subdue modelled farm output price hikes within TERM-H2O in an extreme drought simulation. That is, allowing excess capacity in downstream processing sectors would reduce their demand for farm inputs as the scarcity of inputs worsened owing to drought.
Dixon and Rimmer (2010) depicted excess capacity via a theory of sticky capital adjustment. The usual theory (i.e. constant returns) is that industries operate at full capacity, so that used capital (KUjr,t for industry j in region r and time period t) is equal to existing capital (KEjr,t). With a sticky rental adjustment assumption, we can think of the rental rate as a profit markup on variable costs. This markup will adjust downwards slowly in response to excess capacity.
- (1)
- (2)
In Equation (1), Rjr,t and Rfjr,t are the rental rates for industry j in region r and year t in the respective policy and forecast runs.5 Sjr,t is a slack variable, which implements Equation (1), and α a positive parameter. Equation (2) is the capital demand equation in which f is a decreasing function of KUjr,t. During drought, we invoke the sticky rental adjustment mechanism for downstream processing industry j (i.e. Sjr,t = 0). This means that used capital KUjr,t falls relative to existing capital KEjr,t. Instead of responding to reduced farm output by paying much higher input prices, processors reduce capital utilisation. This is equivalent to an inward movement in processing supply curves and an accompanying reduction in demand for farm inputs. While this will have little impact on processing sector output prices, it will reduce the demand for and moderate scarcity-induced price hikes of farm inputs and consequently moderate the fall in the rate of return on capital in the processing sector. In turn, smaller farm output price hikes will moderate terms-of-trade effects in small regions during drought. When better seasons return, the industry resumes full capacity utilisation. In the full capacity state, Sjr,t ≥ 0 and KUjr,t = KEjr,t. The change of state between full capacity (with market-clearing rate-of-return adjustments) and excess capacity (a quantity adjustment) requires the use of a complementarity condition, implemented in the model using GEMPACK software, as described by Harrison et al. (2004).
Why did we not model excess capacity via the inclusion of fixed costs? A number of CGE applications have, including Harris (1984), Abayasiri-Silva and Horridge (1998), and other studies downloadable from the GTAP website: Kharitonov and Walmsley (2004), Kuik and Gerlagh (2005) and Hertel and Swaminathan (1996). Applications that include fixed costs in the model formulation typically apply to relatively small change cases. The inclusion of fixed costs would have further complicated TERM-H2O without guaranteeing a solution in large change simulations. Instead, we followed Dixon and Rimmer (2010), who accepted excess capacity as a real-world phenomenon. Their method concentrates on obtaining a plausible model solution in a large change case without attempting to explain excess capacity.
3. Drought in south-eastern Australia from 2006–07 to 2008–09
- Top of page
- Abstract
- 1. Introduction
- 2. Enhancing the representation of irrigation in TERM
- 3. Drought in south-eastern Australia from 2006–07 to 2008–09
- 4. Conclusions
- References
Bureau of Meteorology data indicate that the entire SMDB basin had either decile one rainfall or the lowest on record for the 3-year period between January 2006 and December 2008 (see Footnote 1). Recurrent droughts affected both dry-land and irrigated production. Dry-land production was most adversely affected in 2006–07 and 2007–08, with a partial recovery in some regions in 2008–09. For irrigators, the impacts of catchment shortfalls on water allocations continued until the flood events of 2010–11. Table 2 shows the modelled percentage shortfalls in water availability by region for 2007–08. We use TERM-H2O with a theory of sticky capital adjustment in some downstream processing sectors to simulate drought impacts. The exogenous policy shocks are the estimated direct impacts on both dry-land productivity and irrigation water allocations from 2006–07 to 2008–09, with an assumed recovery in dry-land productivity in 2009–10 and eventual full recovery in water allocations by 2011–12 (the modelling was completed before the floods of 2010–11).
3.1. Comparing naïve calculations and modelled impacts for 2007–08
We start with an analysis of our results for 2007–08. Lack of rainfall in 2007–08 meant that dry-land productivity in the SMDB was below average. Irrigation allocations were at a low point after two successive years of drought.
We can calculate a naïve or first-guess estimate of the contribution of a farm subset k of all industries j to a percentage change in GDP in region r (gdpr) as:
- (3)
PRIM is the level of value-added output of each sector, and q is the percentage change in output. As a starting point for our naïve calculation, we assume that for irrigation sectors i, qi = xwati where the latter is the percentage difference in water allocations from normal. Additionally, our naïve calculation of lost output in dry-land sectors j equals the technological deterioration owing to drought (aprimj) so that qj = aprimj. Our initial estimate of the impact of drought in which a refers to all industries in region r is:
- (4)
In Table 2, row (1) shows dry-land productivity and row (2) an index of water availability relative to a normal year. Rows (3–5) provide estimates of the contributions of dry-land plus irrigation farming to GDP in each region. Rows (6–8) contain our first-guess contributions of irrigation and dry-land sectors to changes in real GDP in the regions of SMDB. The modelled contributions to changes in regional GDP by broad sector and irrigation water are shown in rows (9–14). Row (15) shows the volume of net water sold by region.
If there were no movements of farm factors including water between sectors, the first-guess impacts on farm sectors shown in rows (6) and (7) would equal the TERM-H2O impacts shown in rows (9) and (10) of Table 2. This would be equivalent to CET parameters for farm sectors being set to zero, with zero substitutability between water and other primary factors. Comparing rows (6) and (9), we see that dry-land first-guess losses predict modelled broad sectoral losses quite closely in some, but not all, regions. Variations arise from some resource movements. In Lower Murrumbidgee, farm factors move from irrigated towards dry-land production as irrigation water is exported to other regions.6 Note that although the contribution of water to regional GDP increases during drought, as its demand is inelastic and therefore its value rises as its availability falls, the contribution to real GDP of water trading is zero. That is, we see the benefits of water trading by comparing the final column entries for rows (10) and (7) in Table 2. Due substantially to water trading (and to a lesser extent, factor substitution away from water), the contribution of irrigation sectors to real GDP in SMDB is −1.9 per cent instead of −3.4 per cent as given by the first-guess calculation.
As mentioned, by comparing rows (9) and (10) with rows (6) and (7) in Table 2, we see the impact of imposing non-zero farm factor CET and CES parameters (and water trading) on the results. What difference would altering the parameters make to results? Our experience with TERM-H2O is that the most important modification necessary to capture observed movements of water as water scarcity changes or relative farm output prices change is the inclusion of CET farm factor movements. Moving from full trading in the SMDB to no inter-regional trading tends to have a bigger impact than parametric variation (within reasonable limits), especially if there are pronounced differences in water allocation shortfalls and productivity losses between regions. Rather than present results of parametric variation here, we instead compare modelled results with actual ABS data later in this section.
We might expect modelled GDP losses in each region to be somewhat larger than our naïve calculation of losses. This is through negative impacts on downstream sectors and the impact of reduced household consumption on service sectors in each region. Modelled GDP losses are larger than our first-guess calculation of losses for some but not all regions shown in Table 2. Water trading between sectors and regions, combined with mobility of farm factors, alleviates some of the losses. For example, Lower Murrumbidgee is a substantial exporter of water to other regions in the drought years of the scenario. The movement of factors including water partly offsets productivity losses and water allocation shortfalls, so that the modelled GDP loss is smaller than the first-guess calculation of the GDP loss in this region. Changes in output by sector in part reflect differences in water's share of total costs, but are also influenced by different demand elasticities and input-substitution possibilities. For example, the dairy and other livestock sectors can substitute between land and cereal inputs.
Finally, in Table 2, we see that the impacts on downstream sectors, although negative, do not imply large regional multipliers. Regional aggregate consumption falls relative to forecast owing to drought. In the short term, when housing stocks, for example, are fixed most adjustment is going to be on housing rentals. Prolonged adverse conditions in MDB regions would lead to long-run quantity adjustments in housing and enlarged negative multipliers overall, but in the short term, price adjustments reduce the size of multipliers driven by the spending effect.
Table 3 compares modelled outcomes for farm products in the SMDB with available data on observed changes. Columns (1–3) show the modelled deviations from forecast owing to drought (versus a hypothetical no-drought baseline for 2007–08), and columns (4–6) estimated actual changes from 2005–06 to 2007–08. Hence, the comparisons are not between like and like, but are the best we can do.
|Modelled outcome deviation from 2007–08 base (%)
|Observed 2007–08 relative to 2005–06 (%)
|Water used†
|Water used†
|Dairy cattle
|Other livestock
|Other agriculture
Cereal production did not shrink as much in the observed period as we modelled. This reflects soaring cereal prices in the observed period: the actual price increase was twice the modelled drought-induced price increase. World prices of cereals in 2006–07 were driven up by increased use of bio-fuels and other international developments beyond price increases arising from drought within Australia. The output outcomes for dairy cattle, grape and fruit turned out better than we modelled, again with observed prices rising more than the modelled deviation. Yet, dairy cattle's use of water dropped more than we modelled: this reflects a larger than modelled movement from irrigated to dry-land production. As dairy output prices were high in 2007–08, dairy producers were willing to move to dry land and pay for cereal feed (grains and hay). Although the observed value of dairy cattle output rose by 1.9 per cent (Table 3, column (4)), the value added almost certainly dropped significantly, reflecting high feed costs and bringing the observed result closer to the modelled result. Overall, there was a greater movement of water out of rice production than we modelled.
Other than rice (for which the commodity price hike was smaller than modelled), only vegetables and the relatively small other agriculture sector did worse than modelled. Observed vegetables output did marginally worse than the modelled outcome because of the observed output price hikes of competing more export-oriented products. The other agriculture sector includes nursery products: Australia's mainland capitals with the exception of Darwin all faced water restrictions in this period, which drove down demand for this sector from household gardeners.
Next, we examine water prices. We would expect water prices to have increased between 2005–06 and 2007–08 by a larger amount than modelled, because of the observed surge in commodity prices for some major irrigation products. This is so: the modelled increase was $285 per megalitre relative to forecast in 2007–08, compared with an observed increase in the Goulburn region relative to 2005–06 of around $500 per megalitre. A weakening of commodity prices in 2008–09 resulted in the price of water falling to $275 per megalitre above 2005–06 levels, closer to the modelled outcome (Watermove weekly data, downloaded from http://www.watermove.com.au, authors' calculations).
The Australian Water Market Report for 2007–08 shows an observed pattern of net downstream trade (National Water Commission 2009). Small amounts were transferred out from the upper Murray reaches in both NSW and Victoria (that is, the Ovens-Murray and Albury-Upper Murray regions, Figure 1), and larger amounts from the Goulburn and lower NSW Murray reaches. The largest net seller was the Murrumbidgee valley, reflecting the influence of rice. Rice is grown in better years; however, a moderate worsening of water scarcity is sufficient to make it more profitable for growers to sell their water allocation for a year than to continue growing rice. The buyers of water were the Victorian Mallee regions and most notably South Australia. In terms of how the modelling replicated this pattern, the main differences are that the model projected higher than observed net water exports from the Murrumbidgee regions and lower than observed net imports to South Australia. The latter was because partly of purchases by the South Australian government. In 2008–09, the observed pattern of water trading moved closer to that modelled by TERM-H2O. The Ovens-Murray region became a net importer of water as modelled (Table 2, row (14)).
3.2. Dynamic analysis of drought followed by a prolonged recovery
Our simulation consists of widespread drought conditions from 2006–07 to 2008–09, with a dry-land recovery in 2009–10 but some delay before the restoration of full water allocations for irrigation sectors. As shown in Table 3, real GDP in SMDB fell 5.7 per cent below forecast in 2007–08 owing to drought. The simulated outcome for 2009–10 remains below forecast because of irrigation water not being fully restored (Fig. 2).
In subsequent years, as a consequence of sharp falls in investment during the drought years, aggregate capital stocks persist below forecast (−0.12 per cent in 2017–18). Similarly, employment does not recover fully in the simulation period. SMDB employment fell to 1.3 per cent below forecast in 2007–08, equivalent to 6000 jobs. Even in 2017–18, long after the recovery, employment persists at 0.36 per cent (around 1500 jobs) below forecast.7
Figure 3 shows the impact of drought on downstream processing sectors in SMDB. In the initial year of drought (2006–07), capital stocks do not change in response to drought. They are pre-determined by the link between current period capital stocks, lagged capital stocks net of depreciation and lagged investment. However, by introducing a theory of excess capacity to the model, we allow a temporary gap to occur between available and used capital for downstream processing sectors. This gap gradually closes between 2006–07 and 2008–09 as falling investment erodes the capital base. With a substantial recovery in 2009–10, the gap is eliminated and the usual theory of constant returns to scale is resumed within the model. The prolonged drought and irrigation water allocation shortfalls have a negative impact on farm investment, so that farm capital persists at almost 2 per cent below forecast in 2017–18.
4. Conclusions
- Top of page
- Abstract
- 1. Introduction
- 2. Enhancing the representation of irrigation in TERM
- 3. Drought in south-eastern Australia from 2006–07 to 2008–09
- 4. Conclusions
- References
The significant contribution of this study is to model very large inward supply shocks to estimate the impact of drought in the SMDB on regional economies. Drought is an inevitable part of farming, but few studies report on the economy-wide modelling of drought impacts. Modellers face obstacles in reaching realistic solutions in drought simulations. In TERM-H2O, it is necessary to introduce excess capacity to downstream processing sectors to keep farm output price hikes within realistic bounds in response to drought-induced shrinkages in farm supplies.
The main finding of this study is that in the short term, drought across the SMDB reduces employment relative to forecast by around 6000 jobs. Even after a return to average seasons, the impacts of drought remain. Depressed farm investment during drought results in farm capital persisting below baseline levels, even many years after drought has ended. Consequently, employment in SMDB does not return to baseline levels but remains at 1500 jobs below forecast in 2017–18. The same model indicated only modest job losses in SMDB arising from increased environmental flows implemented through buyback (Dixon et al. 2011). No other model used to estimate the regional employment consequences of buyback or similar policy proposals has been tested in a drought scenario.
It is possible to check some results against actual outcomes. TERM-H2O results relative to forecast for 2007–08 give a reasonable account of observed changes from 2005–06 to 2007–08. Most differences between modelled and observed outcomes arise from global conditions that were not included in the drought scenario. For example, world grain and dairy output prices rose strongly in 2007–08. For these commodities, TERM-H2O predicted a larger decline in output and smaller hike in prices than observed. Consequently, TERM-H2O underestimated the dollar per megalitre rise in the price of irrigation water for 2007–08, yet tracked the irrigation water price reasonably in 2008–09 when grain and dairy prices fell.
At the sub-state level, data on employment numbers are harder to obtain between censuses. The ABS conducts the Labour Force Survey regularly but data are state-wide estimates. Beyond anecdotes and other employment estimates that are certain to be patchy rather than comprehensive, a better picture of the impact of drought on SMDB may have to wait until small region employment by industry numbers appear after the 2011 census.
It appears highly probable that as the current policy of purchasing water from farmers for environmental flows continues in the Murray-Darling basin, the claims of thousands of job losses arising from the policy will not stand up to scrutiny. Even using a simple calculation based on farm shares of regional GDP, the regional economic impacts of drought are many-fold worse than the probable impacts of water buybacks. It is possible that a high Australian dollar will impose greater difficulties on SMDB farmers in the present decade than either drought or water buyback policy.
- 1
A map showing rainfall deciles for the 3 years ending December 2008 is downloadable from http://www.bom.gov.au/jsp/awap/rain/archive.jsp?colour=colour&map=decile&year=2008&month=12&period=36month&area=nat.
- 2
In TERM-H2O, irrigation sectors require a fixed volume of water per hectare. When water scarcity worsens, either irrigable land re-allocates to activities that require less water per hectare or irrigable land switches to dry-land farming. Dry land cannot be used in irrigation activities.
- 3
Farm income in the Murray statistical division in the 2006 TERM database accounted for around 12 per cent of total regional income. One town, Albury, accounts for 40 per cent of the population of Murray (Australian Bureau of Statistics (ABS) 2009b). Within the Murray statistical division, the farm share of GDP excluding Albury SSD (i.e., the Central Murray and Murray-Darling statistical sub-divisions) exceeds 20 per cent.
- 4
Dixon and Rimmer (2002, pp. 222–225) derive a formula for export demand elasticities based on import substitution equations. This formula makes such elasticities in a national model consistent with the Armington parameters in a global model such as GTAP.
- 5
In dynamic modelling, we run a baseline forecast and a policy run. In the case of an adverse event such as drought, the 'policy' run is more accurately labelled the 'perturbation' run.
- 6
The solution procedure is Euler 60-steps (and Euler 256-steps in the first 4 years of drought and recovery), used to eliminate solution errors from the linearised model in this large change simulation (Dixon et al. 1982, chapter 5).
- 7
National employment is exogenous in the policy simulation. Regional labour markets follow the national wage, so that all regional adjustments are via labour movements rather than regional wage differentials. Another version of dynamic TERM includes a theory of regional sticky wage adjustment (Wittwer et al. 2005).
- Top of page
- Abstract
- 1. Introduction
- 2. Enhancing the representation of irrigation in TERM
- 3. Drought in south-eastern Australia from 2006–07 to 2008–09
- 4. Conclusions
- References
- ABARE (Australian Bureau of Agricultural and Resource Economics) (2009). Australian Commodity Statistics 2009. ABARE, Canberra.
- ABARE–BRS (Australian Bureau of Agricultural and Resource Economics and the Bureau of Rural Sciences) (2010). Environmentally sustainable diversion limits in the Murray Darling Basin: socioeconomic analysis. Report to MDBA, Canberra, October.
- 1998). Economies of scale and imperfect competition in an applied general equilibrium model of Australia, in Arrow, K., Ng, Y.-K. and Yang, X. (eds), Increasing Returns and Economic Analysis. Macmillan Press Ltd., Great Britain and St. Martin's Press, Inc., New York, pp. 307–334. and (
- ABS (Australian Bureau of Statistics) (2009a). Experimental Estimates of the Gross Value of Irrigated Agricultural Production, 2000–01 to 2006–07, Catalogue 4610.0.55.008, Australian Bureau of Statistics, Canberra.
- ABS (Australian Bureau of Statistics) (2009b). Value of Agricultural Commodities Produced, Australia, 2007–08, Catalogue 7503.0, Australian Bureau of Statistics, Canberra.
- 2010). Farmers pour scorn on Murray-Darling water blueprint. The Australian, October 13. (
- 2010). Economic Contributions and Characteristics of Grapes and Wine in Australia's Wine Regions. Wine Economics Research Centre Working Paper No. 0110, University of Adelaide, Adelaide. , , and (
- 1969). The Geographic Pattern of Trade and the Effects of Price Changes, IMF Staff Papers XVI, 176–199. (
- 1970). Adjustment of Trade Balances: Some Experiments with a Model of Trade Among Many Countries, IMF Staff Papers XVII, 488–523. (
- 2002). Dynamic General Equilibrium Modelling for Forecasting and Policy: A Practical Guide and Documentation of MONASH, Contributions to Economic Analysis 256, North-Holland, Amsterdam. and (
- 2010). You can't have a CGE recession without excess capacity, Economic Modelling 28, 602–613. and (
- 1982). ORANI: A Multisectoral Model of the Australian Economy. Contributions to Economic Analysis 142, North-Holland, Amsterdam. , , and (
- 2010). Modelling the Australian government's buyback scheme with a dynamic multi-regional CGE model, Monash University, Centre of Policy Studies Working Paper G-186. , and (
- 2011). Saving the Southern Murray-Darling Basin: the economic effects of a buyback of irrigation water, Economic Record 87, 153–168. , and (
- 1983). Drought assistance policy, The Australian Journal of Agricultural Economics 27, 185–199. (
- 1984). AGE analysis of small open economies with scale economies and imperfect competition, American Economic Review 74, 1016–1032. (
- 2004). A practical method for explicitly modeling quotas and other complementarities, Computational Economics 23, 325–341. , , and (
- 1996). Introducing Monopolistic Competition into the GTAP Model. GTAP Technical Paper No. 06. and (
- 2005). Using a highly disaggregated multi-regional single-country model to analyse the impacts of the 2002–03 drought on Australia, Journal of Policy Modelling 27, 285–308. , and (
- 2004). Impact of Russia's WTO Accession on the Structure of the Russian Economy. Presented at the 7th Annual Conference on Global Economic Analysis, Washington DC, USA. and (
- 2005). PSR Emissions Trading: An Alternative for Conventional Emissions Trading that would Prevent Carbon Leakage and Protect Exposed Sectors of Industry? Presented at the 8th Annual Conference on Global Economic Analysis, Lübeck, Germany. and (
- 1987). The Australian economy in the very long run, in Maddock, R. and McLean, I. (eds), The Australian Economy in the Long Run. Cambridge University Press, Cambridge, pp. 5–29. and (
- National Water Commission (2009). Australian Water Markets Report 2008–2009. National Water Commission, Canberra.
- 1998). Evolution of drought policy and related science in Australia and South Africa, Agricultural Systems 57, 231–258. , and (
- 2010). The economic costs of extreme weather events: a hydro-meteorological CGE analysis for Malawi, Environment and Development Economics 16, 177–198. , , and (
- 2010). The potential effects of changes to water allocation policy on financing the agricultural sector and businesses in the Murray-Darling basin. Report prepared for the Murray-Darling Basin Authority, October. (
- 1991). The economic impact of crop losses: a computable general equilibrium approach, Western Journal of Agricultural Economics 16, 144–155. , and (
- Sunrice (2010). SunRice announces Deniliquin Mill will reopen in 2011, Available from URL: http://www.sunrice.com.au/uploads/MR_-_Deniliquin_Mill_to_Re-open.pdf.
- 2003). An outline of TERM and modifications to include water usage in the Murray-Darling Basin. Available from URL: http://www.monash.edu.au/policy/archivep.htm TPGW0050. (
- 2005). The regional economic impacts of a plant disease incursion using a general equilibrium approach, Australian Journal of Agricultural and Resource Economics 49, 75–89. , and (
- 2006). Without Water: The economics of supplying water to 5 million more Australians, CSIRO Land and Water and Centre for Policy Studies. Available from URL: http://www.myoung.net.au/water/publications/WithoutWater.pdf. , , and (

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Daniel Davidson
Daniel Davidson has undergraduate and graduate degrees in humanities-related subjects. He has been active for a number of years in researching issues related to design, creation, and evolution.
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Six girls from Troop 9327 developed a scavenger hunt patch program for the Alabama Department of Archives and History. The girls developed the pamphlet for the hunt, which walks participants through the Hands on Gallery and the Museum of Alabama. The girls also designed the patch, and donated the design to the Department.
The Girl Scouts chose this idea from a list of options they developed with a focus on providing enrichment activities to older kids' groups. They worked on their project during their regular meetings - this helped them to set target dates and goals, and to stay on track.
The girls state that, through their Silver Award project, We learned a lot about Alabama history. We had to go to the Museum of Alabama so many times to develop the questions and test the scavenger hunt that we feel like we have memorized us. You can ask us how many pigs are in the diorama or how to make cornbread in the 1800's and we can tell you! We also learned about how to plan long-range and work with a group."
The Girl Scouts hope that older kids will appreciate the Museum of Alabama, and provide some funds for the ADAH too. They are very proud of their project.
Nicole's Take Action Project brought together elementary school students who were struggling in reading with a patient, kind, and nonjudgmental listener -- a dog named Hoss. This positive, encouraging (and fun) environment helped these students improve their reading scores by up to 50%.
Nicole has been a Girl Scout for 13 years, and has gone from attending programs and events to organizing several for her sister Girl Scouts. She has earned her Bronze and Silver Awards.
Nicole will graduate from Spanish Fort High School. She plans on attending Auburn University to study Microbiology, and then on to veterinary school, with the ultimate goal of opening her own small animal clinic. Her proud parents are John and Vicki Nobles of Daphne.
How did you come up with your idea?
I am very passionate about reading and animals so I wanted to come up with a creative way to combine the two. I came up with the idea to start this reading program after a great deal of research on illiteracy in our area. I also began to realize that even students in my classes had problems reading out loud because they were uncomfortable. I decided that making a reading program for elementary school students would be the most beneficial way to encourage students and improve their reading abilities while they are still impressionable.
Were you intimidated by the scale of the project? was initially intimidated by this project, but as I began I realized that the people I was working with would help through all of the challenges.
How did you keep up the momentum for the project? I kept the momentum by getting new people involved with my project and teaching others about the mission of my project.
Were you ever discouraged? If so, what did you do to overcome that? I was not really discouraged through the project, but just challenged.
Can you tell us a little story about some part of your project that was special to you?
The best part of my project was seeing the kids' faces each week when they found out that Hoss was there. Each week they would run down the hallways to see who could get to him first. The first graders were also extremely funny because they would always rush to see who could say "The End" first when they finished their stories. All of the kids were so cute and smart; I had so much fun with them each week.
How will people benefit from this? The students will benefit because their confidence will be boosted and their reading abilities will be improved. Their increased confidence in their reading abilities will also help them succeed in their other subjects in school.
How did you feel after you finished? After I finished my project I felt very accomplished, because I had created a program that will be sustained in SFES and is spreading around the county. I am also exhilarated that this project has helped the students so much and will continue to help other students.
What advice would you give to other girls considering a Gold? I would suggest that they begin thinking about it early and make sure that they work on something they are passionate about. If you are not passionate about this project it will not be as successful and it will not mean as much to you. It is also important that you find people to work with that are also passionate about your project because that will also ensure that your project is successful and long lasting.
Your Gold Project made a change for the better in your community. Did it change you? If so, how? This project did change me, not only did it teach me how to stick with a project this big, but the kids also taught me how to be happy with the little things in life. The students each week had a new story to tell and something they had to share with Hoss. This taught me that sometimes the most important things in life are the small, everyday activities that go unrecognized.
Abby's Take Action Project, The Buddy System, is a program that partners elementary age students with high school students for tutoring sessions. Each tutor works specifically with one student in order to learn that child's learning styles and serve as a role model for that child.
Abby began her Girl Scout Journey as a Brownie, and became a Girl Scout lifetime Member upon graduation.
Abby's parents are Jim and Stacy Legge of Spanish Fort. Abby graduated from Spanish Fort High School in 2015 and will attend Mississippi State University, majoring in Secondary Education and Mathematics.
How did you come up with your idea?
- The spring of my junior year I was hired to tutor a third grade boy. As I worked with him, I recognized that he wasn't dumb or slow, he just needed one person to sit down and work individually with him. As the semester went on, and as getting to know him better, it became easier to recognize what helped him and what tricks helped him learn better. I recognized that there are a lot of other children who will go without that help and will continue to struggle, so I decided to do something about it.
Were you intimidated by the scale of the project?
- Of course! In other service projects or clubs you have a role or a job. In the Gold Award Process, you are the secretary, treasurer, president, and volunteer all wrapped in one. Instead of just being able to focus on just one part, you have to focus on every possible aspect of the project you are starting.
How did you keep up the momentum for the project?
- Stay positive and remember why you are doing this. My motto was "It's for the kids." Also, make sure you schedule in work and play. If you try to do all the hard parts first, it becomes discouraging. Make sure you participate in the fun parts as well.
Were you ever discouraged? If so, what did you do to overcome that?
- At first, when I was originally discussing the idea with the principals of both the high school and elementary school, they were skeptical. Not because they didn't believe my idea was good, but they have to be the practical ones and ask the hard questions. I just reminded myself that I had answers for their questions, and I kept emphasizing the impact the project would make.
Can you tell us a little story about some part of your project that was special to you? Something funny, or touching, or that went terribly wrong and how you fixed it?
The funniest child I worked with throughout the year's name was Jaden. He looked at me and asked me during the end of a tutoring session if we would be back next week. I replied that we would and Jaden said that that was "tight", meaning that he was excited and was enjoying the program. I replied, "your right, it is Tight". He looked at me very seriously and replied, "Don't say that. You have to be cool when you say something is 'tight'." So for the rest of the semester, each week I received my own tutoring lessons on how to speak "cool".
How will people benefit from this?
- The elementary age students will become better in their math and English skills as well as develop a bond with a student tutor. The tutor will get accountable service hours and the chance to be a mentor and a help to someone who looks up to them.
How did you feel after you finished?
- Calm. Relieved. Positive. I am calm and relieved because my hard work payed off. Those kids are happy, so I'm happy. Positive because everyone wants to leave some sort of legacy behind. When I leave for college, I may not be remembered by peers or teachers, but the kids I partnered with will always know that I helped them.
What advice would you give to other girls considering a Gold Award)?
- There will be times when you ask yourself...Is it worth the award? Couldn't I just do the project and not get the silly little pin? You could, but I say it will lose some of its significance. Not every Girl Scout stays in long enough to reach for their Gold. The Gold Award is more for you to look at yourself and say, "I did it." I spent 10 or more years working toward this and look at the young woman I have become!
Your Gold Project made a change for the better in your community. Did it change you? If so, how? Did you learn new skills, or change your outlook on an issue? What will you take away from this experience?
- I learned a lot of organization skills. I talked with people through countless emails and phone calls and remembering who said what could get confusing.
As a Girl Scout I was chosen as Press Rep to say a prayer in front of the legislators in Montgomery. It was a very wonderful opportunity. Two other press reps said the pledge. It was kind of scary but it was actually pretty fun because we got to meet the Secretary of State.
There's a lot of history behind the state of Alabama that I never knew of. I also got to try the North-Central Girl Scouts of Alabama types of Girl Scout cookies, like the Savannah Smiles cookie.
My favorite place in the State House is the voting room called the Senate. We talked about Governor Robert Bentley. The Secretary of State, John Merrill said that he has met President Ronald Reagan and Hillary Clinton and many more politicians and Presidents.
The girls and I got to skip school but it was worth it. You should go to Montgomery, too! The people that work at the State house are very nice and you should go there and meet them to learn about the wonderful politicians of our great state.
-- Press Rep Tristan


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I was working in San Diego and was looking for a suite hotel near a gym and a Starbucks. This gym fit the bill.
The hotel looked to be new along with most of the development in the area. The staff is very friendly and efficient. Check-in process went well.
There is a Starbucks just on the other side of the parking lot that is open at 4:30 AM. Nice for me as I was staying on east coast time. In addition there is a great 24 hour gym (1265 Laurel Tree Lane Suite 100 Carlsbad, CA 92011) nearby that only charged $30 for the week.
I was getting up early (2 AM) so the commune to La Jolla took about 20-30 minutes, but if you leave later expect it to be at least double that time.
This hotel does serve hard boiled eggs as part of the free breakfast.
The laundry room was large and the machines that I used were working fine. They also having a vending machine for laundry supplies in the launder room do you do not have to go to the front desk.
The hotel also has a nice small pool area.
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The penalized likelihood method is used for a new semi-parametric software reliability model. This new model is a nonparametric generalization of all parametric models where the failure intensity function depends only on the number of observed failures, viz. number-of-failures models (NF). Experimental results show that the semi-parametric model generally fits better and has better 1-step predictive quality than parametric NF. Using generalized linear models, this paper presents new parametric models (polynomial models) that have performances (deviance and predictive-qualities) approaching those of the semi-parametric model. Graphical and statistical techniques are used to choose the appropriate polynomial model for each data-set. The polynomial models are a very good compromise between the nonvalidity of the simple assumptions of classical NF, and the complexity of use and interpretation of the semi-parametric model. The latter represents a reference model that we approach by choosing adequate link and regression functions for the polynomial models
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132 Reviews
I really didn't know what to expect since no one really described the taste or texture of the cookies. They are like little cakey sugar drop cookies that taste fruity. I used berry jello and I rolled the walnut-size balls in powdered sugar before baking. I'm not sure why but I had to bake them for more like 15-17 minutes, not 6 - 8 like the recipe says. This would be even better if you could figure out somehow to make them a little more tart. Like lemon jello with lemon peel maybe? I'll try that next time. A yummy, soft, sweet cookie. Oh - and as everyone else mentioned, the color is nice and vibrant, too.
Great cookies! I made two batches.....one in the cookie press, which worked beautifully with this dough (don't chill dough). I used cherry Jell-o. The second batch, I omitted the Jell-o and substituted 1/2 cup sugar, added 1 tsp. of vanilla, and pressed balls to about 1/4 inch thickness with a sugared flat-bottomed glass. It made great sugar cookies. Thanks for the recipe!
I have been making these cookies (we called them Pastilles) for over 10 years but lost the recipe last Christmas. Now I can make them again--thanks! (In fact I have some baking now!) My recipe said to roll them in granulated sugar, then put them on the baking sheet and flatten them with the bottom of a glass. (That works well!)
I made these for my daughters 3rd b-day party. Everyone loved them. Because the theme was butterfly I made 2 flavors strawberry and berry. I was so excited to see that the pink and green when mixed together looked marbled and held their color without blending into a grey blob. I added some extra flour and chilled then rolled on a flour surface to make cut outs of butterfly's! Perfect and they were awsome!!!!
i have made these for years as christmas cookies. i use a cookie press and make all kinds of shapes. my favorite flavors are strawberry banana and apricot. yum.
I made a batch yesterday as my contribution to the Afterschool Club at my church; and since it's a group of 7-13 years old kids, I used strawberry jello, but skipped the nuts. There is always the possibility of passing on the nut allergy; and if it's optional, I prefer not to take any chances with kids. Since I sell Watkins; and have access to a variety of extracts, I think I would substitute one of our extracts for the vanilla next time, such as strawberry instead of vanilla. I also appreciated the fact that the cookie dough mixed up so easily, instead of making sure to use my stand mixer to get all the flour mixed in properly. I am sure it will be good to vary the jellos according to what is most available, I might try even try using wild raspberry next time.
I made cranberry, because that's what I had and they turned out great! I sprinkled them with a bit of powdered suger. Yum. I see a sure favorite for anytime of year in this recipe.
These are truly the perfect addition to a xmas cookie tray, although I intend to make these all year long! They're very easy, tasty, and, of course, colourful. I used real butter instead of margarine, and let the dough chill in the fridge for 20 minutes before shaping into balls. Add this one to your cookbook; you'll love it!
Very pretty, very rich tasting little cookie. Impressive too. I found that letting the dough chill for 30 minutes to an hour helps in the shaping of these cookies. I used cherry jello & these cookies were so pretty. Also sprinkled a bit of regular sugar on the tops before flattening with a fork. I'll be making lime jello cookies to fit in with the Holiday collection!
Nice change of pace. I used strawberry jello and added some strawberry preserves (approx. 2T). Turned out I had some semi-sweet chocolate morsels so I sprinkled a few on top before baking and finished off with confectioner's sugar. Nice presentation for Valentine's Day.


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Tech Thursday: 15% off 1+ Yards of Sport Lycra, Performance Knit & Performance Pique Fabrics Through 11:59 P.M. EDT July 28th.
Designer, embroiderer and busy mom.
I love a blank piece of graph paper; the possibilities are endless. I have a tendency to think in terms of clothing. Something I inherited from my mom. I miss her very much.
© 2008-2015 Spoonflower Inc


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Why Upgrade Campus & Branch Switching & Wireless Infrastructure?Enterprise Networks
Many of the existing switch and wireless infrastructures that were deployed 5 or more years ago were not designedRead More
Enabling the next wave of hyper-context aware mobile experiences: Cisco Enterprise Mobility Services Platform (EMSP)Enterprise Networks
The profound impact mobile devices has had on ITRead More
Top 10 Reasons to Upgrade to the 7.4 MD Software ReleaseMobility
As the famous saying goes, "Good things come to those who wait". Delayed gratification – person's ability to forgoRead More
Common Core Mobile Technology Uplifts School PerformanceEnterprise Networks
Studies show the importance of quality education when it comes to the development of a country. TheRead More
The Cisco IT Story: ITaaS with Cisco Prime Service CatalogData Center
We had some exciting sessions featuring Cisco Prime Service Catalog at Cisco Live Milan a few weeksRead More
CHAOS (Control Havoc and Overhaul Security): The new Order for ITData Center
Mobility and the cloud have changed how we work, transforming pockets of downtime into bursts of productivity, with easyRead More


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NEW! Instant Download is now available!
Dance: Salsa (Now 25% Off!)
Machine Embroidery Design available in 2 sizes:: for large 130 x 180 mm (5" x 7") and mega hoops.Old Price: $9.99
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Frédéric François Chopin (/ˈʃoʊpæn/; 22 February or 1 March 1810 – 17 October 1849), born Fryderyk Franciszek Chopin, was a Polish composer and a virtuoso pianist of the Romantic era, who wrote primarily for the solo piano. He gained and has mai...ntained renown worldwide as one of the leading musicians of his era, whose "poetic genius was based on a professional technique that was without equal in his generation." Chopin was born in what was then the Duchy of Warsaw, and grew up in Warsaw, which after 1815 became part of Congress Poland. A child prodigy, he completed his musical education and composed his earlier works in Warsaw before leaving Poland at the age of 20, less than a month before the outbreak of the November 1830 Uprising.
Connect any celebrity with Frédéric Chopin to see how closely they are linked... romantically!


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Memorial services for Ernest A. Campbell, 80, who died May 26, 2001, at St. Joseph's Hospital, Tampa, will be held today at 9 a.m. at St. Anastasia Catholic Church.
In lieu of flowers, the family requests that donations be made, in his memory, to St. Anastasia Catholic Church, 5205 A1A South, St. Augustine, 32080.
© 2016. All Rights Reserved. Contact Us


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Author Archives: Margaret Fuhrer
ICYMI: Watch Maddie Ziegler and Sia Perform "Cheap Thrills" on "The Voice"
There's something uniquely satisfying about seeing a great music video reenacted onstage. It's confirmation that the artists involved are just … More »
Celebrate #TutuTuesday with Our Best Tutu Stories
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This Syncopated Ladies Prince Tribute Is Perfection
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That Time a Patriots Tight End Took Class with a Miami City Ballet Star
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Estonian Military Faces Staff Drain on Low Wages, Postimees Says
Estonia's senior military personnel is increasingly leaving for private-industry jobs as a result of rising income disparities, Postimees reported, citing data and interviews with former military officers.
Almost 400 officers resigned last year, the most since at least 2006, according to the Tallinn-based newspaper. The government has no funds to raise military wages until next year, Defense Minister Urmas Reinsalu was cited as saying by Postimees.
Before it's here, it's on the Bloomberg Terminal. LEARN MORE


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Our team of dedicated electrical technicians has over 200 years of combined experience in the wiring and assembly of a broad range of control panel applications. All panels are assembled to meet NEMA & IEC standards.
From increased safety control panels to motor starters, circuit breaker assemblies, purge systems, PLC and GUI panels and operator consoles we are committed to meeting your technical requirements, schedule and budget.
We have served the electrical industry since 1969, and approach each project, from single panel enclosures to large scale custom electrical panels, with the same dedication to craftsmanship. We will build to your specifications from any cad design or from your functional description.
Whether your application requires a NEMA 4, NEMA4X, NEMA12 or NEMA 7, we provide you with competitive pricing and high quality services to suit your needs.
We welcome all inquiries. Call us today for a quotation on your project.
Take a look at our photo collection of a few of our previous jobs.


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OpCodes.Ldarga_S Field
Assembly: mscorlib (in mscorlib.dll)
The following table lists the instruction's hexadecimal and Microsoft Intermediate Language (MSIL) assembly format, along with a brief reference summary:
Assembly Format
0F < unsigned int8 >
ldarga.s index
Fetch the address of argument indexed by index, short form.
The stack transitional behavior, in sequential order, is:
The address addr of the argument indexed by index is pushed onto the stack.
ldarga.s (the short form of ldarga) should be used for argument numbers 0 through 255, and is a more efficient encoding.
The ldarga.s instruction fetches the address (of type *) of the argument indexed by index, where arguments are indexed from 0 onwards. The address addr is always aligned to a natural boundary on the target machine.
For procedures that take a variable-length argument list, the ldarga.s instruction can be used only for the initial fixed arguments, not those in the variable part of the signature.
ldarga.s is used for by-ref parameter passing. For other cases, Ldarg_S and Starg_S should be used.
The following Emit method overload can use the ldarga.s opcode:
ILGenerator.Emit(OpCode, byte)
Windows 98, Windows Server 2000 SP4, Windows Millennium Edition, Windows Server 2003, Windows XP Media Center Edition, Windows XP Professional x64 Edition, Windows XP SP2, Windows XP Starter EditionThe Microsoft .NET Framework 3.0 is supported on Windows Vista, Microsoft Windows XP SP2, and Windows Server 2003 SP1.


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Bluebeam Revu CAD 2016
Bluebeam PDF Revu for AutoCAD, Revit, Navisworks Manage, Navisworks Simulate, SolidWorks, SketchUp Pro and MS Office.Bluebeam Revu CAD 2016 One Seat (Quantity 1-4 seats) improves communication, productivity and collaboration on projects by enabling digital processes from design, through bid and build. The professional PDF solution for CAD users, Bluebeam Revu CAD 2016 One Seat (Quantity 1-4 seats) provides powerful PDF creation, markup and editing features for a paperless workflow.
Use Bluebeam's plugins for AutoCAD, Revit,Navisworks Manage, Navisworks Simulate, SolidWorks and MS Office for one- button PDF creation and batch options, or use the Bluebeam PDF printer to convert other CAD and Windows files to 10 different file formats. Create and view 3D PDFs and redline PDF drawings with industry standard markups. Assemble PDF submittals and bid sets, perform cost calculations, automatically compare drawings, integrate with SharePoint or ProjectWise, go mobile on a tablet PC and collaborate in real time with Bluebeam Studio.
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Hailing from Olympia, Washington, LAKE has a refreshingly un-ironic and musically solid take on mixing together indie pop with R&B for a sound that is essentially blue-eyed soul. The delicate harmonies and infectious melodies present in most of the band's material are reminiscent of popular songs of the '70s, without the bombast or ersatz excitement. With Karl Blau as a collaborator, LAKE's songwriting is also infused with a touch of hip-hop in the vocal phrasings and the rhythms. There is a disarming wholesomeness and purity to the act's music that sounds like you're hearing a group of session musicians playing catchy music they love instead of the songs they're paid to perform.
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