{'fraction_non_alphanumeric': 0.01694915254237288, 'fraction_numerical': 0.0, 'mean_word_length': 5.688679245283019, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
SPATIAL ANALYSIS OF POVERTY: THE CASE OF PERU

The concept of Multidimensional Poverty traditionally was used for comparative analysis across regions or countries. This paper uses the concept of Multidimensional Poverty for each Peruvian region to analyzes spatial patterns, spatial autocorrelation, and identifies spatial spillovers in poverty. We find evidence of statistically significant spatial autocorrelation across regions; in other words, poverty has spatial effects. In more detail, we find that those spatial spillovers are originated in the error terms rather than the endogenous variable. Also, the covariates we use in our regressions are statistically significant and stable across the models.