Three essays on applied economics

Abstract

This thesis focuses on the application of empirical research methods to different economic topics. The first chapter examines production effects of subsidies with different characteristics. The second chapter evaluates the impact of an oldage pension program on the welfare of the recipient’s family members. The third chapter applies an income inequality model to study the influence of differences in citation practices across scientific fields on the overall citation inequality. Chapter 1, “Differential Effects on Output Levels of Binding and non-Binding Subsidies under Capitalization”. Subsidies on outputs or inputs are usually production-promoting by lowering the marginal cost. However, if subsidies are binding, i.e. outputs or inputs are partially subsidized, subsidies don’t affect the output level. If subsidies capitalize into input prices, i.e. subsidies benefit both the recipients and input providers, outputs will be negatively affected. My paper contributes by empirically assessing production effects of subsidies taking into account both bindingness and capitalization. I study cattle payments under the Common Agricultural Policy (CAP) implemented in the European Union (EU). I set up a simple model to analyze production effects of these payments. I also estimate the effects with Spanish farm-level data. CAP 1992 and Agenda 2000 are two policy programs of the CAP. Both are designed to reduce over-production in agriculture. Estimation results suggest that cattle payments have negative impacts on outputs when they are binding under CAP 1992, and positive impacts when they are non-binding under Agenda 2000. Chapter 2, “Reassessing the Differential Impact of Grandmothers and Grandfathers: The Old Age Program in Nepal” (co-authored with Ricardo Mora). We study the effects on infant mortality of the introduction in 1995 of a non-contributory universal pension scheme in Nepal known as the Old age Allowance Program. We use cross-sectional data from the 1996 and 2001 Nepal Demographic and Health Surveys. Following a standard diff-in-diffs approach, we find positive and significant effects on survival rates for the presence in the same household of a female beneficiary while negative and sometimes significant effects for the presence of a male beneficiary. When we conduct pre-treatment common trend tests, we find that we cannot reject it for the case of the female beneficiaries but we strongly reject it for the case of male beneficiaries. Following Mora and Reggio (2012), we then propose a more flexible model and identification strategy and find that there are no differences in the female and the male beneficiary effects. We interpret these results as suggestive that cross-sectional analysis may bias downwards the estimates of the effect of grandfathers because of gender differences in endogenous household formation. Chapter 3 is a combination of two closely related papers, namely “The Measurement of the Effect on Citation Inequality of Differences in Citation Practices across Scientific Fields” (co-authored with Juan A. Crespo and Javier Ruiz-Castillo, published in PLoS ONE 8(3): e58727 (2013)), and “The Effect on Citation Inequality of Differences in Citation Practices at the Web of Science Subject Category Level” (co-authored with Juan A. Crespoa, Neus Herranz and Javier Ruiz-Castillo, published in Journal of the American Society for Information Science and Technology, 65:1244-1256, (June 2014)). We introduce a novel method for measuring which part of overall citation inequality can be attributed to differences in citation practices across scientific fields. In addition, we implement an empirical strategy for making meaningful comparisons between the numbers of citations received by articles in different scientific fields. Using a dataset of 4.4 million articles published in 1998-2003 with a five-year citation window, we find that differences in citation practices between the 22 fields account for about 14% of overall citation inequality. When the classification system goes from 22 fields to 219 sub-fields, the effect on citation inequality increases to about 18%. For comparisons of citation counts across fields, we provide a set of exchange rates (ERs) to express citations in any field into citations in the all-fields case. When the raw citation data are normalized with our ERs, the effect of differences in citation practices is reduced to around 2% of overall citation inequality in the case of 22 fields. In the case of 219 sub-fields with the fractional strategy, the normalization of the raw data using the ERs (or sub-field mean citations) as normalization factors reduces the effect to 3.8% (3.4%) of overall citation inequality. The results with the fractional strategy are essentially replicated when we adopt a multiplicative approach.