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Statistically Matching Income and Consumption Data : An Evaluation of Energy and Income Poverty in Romania

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  • Britta Laurin Rude
  • Monica Robayo

Abstract

To design effective policy instruments that target the energy poor in Romania, it is crucial to understand who the energy poor are. However, these types of analyses are limited by the current data environment. While monetary energy poverty estimates rely on data from expenditure surveys, traditional welfare indicators and detailed information on access to social protection programs form part of the EU-SILC. Samples of both surveys differ; consequently, record linkage of both surveys is impossible. This paper propose an alternative solution to combine information from both surveys, namely statistical matching techniques. It applies several imputation models to impute information on energy spending shares from the HBS into the EU-SILC based on a set of matching variables, compare the performance of these models and apply the best-performing one. Based on the resulting matched dataset, the results show that nearly all the monetary poor are also energy poor, but that a significant additional share of the population in Romania is energy poor. Energy poverty rates are higher at the lower end of the welfare distribution. This result has significant welfare implications.

Suggested Citation

  • Britta Laurin Rude & Monica Robayo, 2024. "Statistically Matching Income and Consumption Data : An Evaluation of Energy and Income Poverty in Romania," Policy Research Working Paper Series 10917, The World Bank.
  • Handle: RePEc:wbk:wbrwps:10917
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    References listed on IDEAS

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    1. Anil Alpman, 2016. "Implementing Rubin's alternative multiple-imputation method for statistical matching in Stata," Stata Journal, StataCorp LLC, vol. 16(3), pages 717-739, September.
    2. Moriarity, Chris & Scheuren, Fritz, 2003. "A Note on Rubin's Statistical Matching Using File Concatenation with Adjusted Weights and Multiple Imputations," Journal of Business & Economic Statistics, American Statistical Association, vol. 21(1), pages 65-73, January.
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    Cited by:

    1. Robayo, Monica & Balaban,Georgiana & Wronski,Marcin, 2024. "Tax Compliance in Romania," Policy Research Working Paper Series 10940, The World Bank.

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