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Working Papers

  • [1901]

    David Martinez-Miera, Rafael Repullo

    Monetary Policy, Macroprudential Policy, and Financial Stability


    This paper reexamines from a theoretical perspective the role of monetary and macroprudential policies in addressing the build-up of risks in the financial system. We construct a stylized general equilibrium model in which the key friction comes from a moral hazard problem in firms' financing that banks' equity capital serves to ameliorate. Tight monetary policy is introduced by open market sales of government debt, and tight macroprudential policy by an increase in capital requirements. We show that both policies are useful, but macroprudential policy is more effective in terms of financial stability and leads to higher social welfare.

  • [1902]

    Samuel Bentolila, Juan J. Dolado, Juan F. Jimeno

    Dual Labour Markets Revisited


    This paper provides an overview of recent research on dual labour markets. Theoretical and empirical contributions on the labour-market effects of dual employment protection legislation are revisited, as well as factors behind its resilience and policies geared towards correcting its negative economic and social consequences. The topics covered include the stepping-stone or dead-end nature of temporary contracts, their effects on employment, unemployment, churn, training, productivity growth, wages, and labour market inflows and outflows. The paper reviews both theoretical advances and relevant policy discussions on a very relevant topic in many European countries, in particular in several that had a very poor employment performance during the recent global economic and financial crisis.

  • [1903]

    Dmitry Arkhangelsky

    Dealing with a Technological Bias: The Difference-in-Difference Approach


    I construct a nonlinear model for causal inference in the empirical settings where researchers observe individual-level data for few large clusters over at least two time periods. It allows for identification (sometimes partial) of the counterfactual distribution, in particular, identifying average treatment effects and quantile treatment effects. The model is exible enough to handle multiple outcome variables, multidimensional heterogeneity, and multiple clusters. It applies to the settings where the new policy is introduced in some of the clusters, and a researcher additionally has information about the pretreatment periods. I argue that in such environments we need to deal with two different sources of bias: selection and technological. In my model, I employ standard methods of causal inference to address the selection problem and use pretreatment information to eliminate the technological bias. In case of one-dimensional heterogeneity, identification is achieved under natural monotonicity assumptions. The situation is considerably more complicated in case of multidimensional heterogeneity where I propose three di erent approaches to identification using results from transportation theory.

  • [1904]

    Esteban García-Miralles, Nezih Guner, Roberto Ramos

    The Spanish Personal Income Tax: Facts and Parametric Estimates


    In this paper, we use administrative data on tax returns to characterize the distributions of before and after-tax income, tax liabilities, and tax credits in Spain for individuals and households. We use the most recent available data, 2015 for individuals and 2013 for households, but also discuss how the income distribution and taxes have changed since 2002. We also estimate effective tax functions that capture the underlying heterogeneity of the data in a parsimonious way. These parametric functions can be used to calculate after-tax incomes in surveys where this information is not directly available, and can also be used in quantitative work in macroeconomics and public finance.

  • [1905]

    Dmitry Arkhangelsky, Guido W. Imbens

    The Role of the Propensity Score in Fixed Effect Models


    We develop a new approach for estimating average treatment effects in the observational studies with unobserved group-level heterogeneity. A common approach in such settings is to use linear fixed effect specifications estimated by least squares regression. Such methods severely limit the extent of the heterogeneity between groups by making the restrictive assumption that linearly adjusting for differences between groups in average covariate values addresses all concerns with cross-group comparisons. We start by making two observations. First we note that the fixed effect method in effect adjusts only for differences between groups by adjusting for the average of covariate values and average treatment. Second, we note that weighting by the inverse of the propensity score would remove biases for comparisons between treated and control units under the fixed effect set up. We then develop three generalizations of the fixed effect approach based on these two observations. First, we suggest more general, nolinear, adjustments for the average covariate values. Second, we suggest robustifying the estimators by using propensity score weighting. Third, we motivate and develop implementations for adjustments that also adjust for group characteristics beyond the average covariate values.

  • [1906]

    Paula Bustos, Juan Manuel Castro Vincenzi, Joan Monras, Jacopo Ponticelli

    Structural Transformation, Industrial Specialization, and Endogenous Growth


    The introduction of new technologies in agriculture can foster structural transformation by freeing workers who find occupation in other sectors. The traditional view is that this increase in labor supply in manufacturing can lead to industrial development. However, when workers moving to manufacturing are mostly unskilled, this process reinforces a country's comparative advantage in low-skill intensive industries. To the extent that these industries undertake less R&D, this change in industrial composition can lead to lower long-run growth. We provide empirical evidence of this mechanism using a large and exogenous increase in agricultural productivity due to the legalization of genetically engineered soy in Brazil. Our results indicate that improvements in agricultural productivity, while positive in the short-run, can generate specialization in less-innovative industries and have negative effects on productivity in the long-run.

  • [1907]

    Dmitry Arkhangelsky, Susan Athey, David A. Hirshberg, Guido W. Imbens, Stefan Wage

    Synthetic Difference in Differences


    We present a new perspective on the Synthetic Control (SC) method as a weighted least squares regression estimator with time fixed effects and unit weights. This perspective suggests a generalization with two way (both unit and time) fixed effects, and both unit and time weights, which can be interpreted as a unit and time weighted version of the standard Difference In Differences (DID) estimator. We find that this new Synthetic Difference In Differences (SDID) estimator has attractive properties compared to the SC and DID estimators. Formally we show that our approach has double robustness properties: the SDID estimator is consistent under a wide variety of weighting schemes given a well-specified fixed effects model, and SDID is consistent with appropriately penalized SC weights when the basic fixed effects model is misspecified and instead the true data generating process involves a more general low-rank structure (e.g., a latent factor model). We also present results that justify standard inference based on weighted DID regression. Further generalizations include unit and time weighted factor models.

  • [1908]

    Natalya Martynova, Enrico Perotti, Javier Suarez

    Bank Capital Forbearance


    We analyze the strategic interaction between undercapitalized banks and a supervisor who may intervene by preventive recapitalization. Supervisory forbearance emerges because of a commitment problem, reinforced by fiscal costs and constrained capacity. Private incentives to comply are lower when supervisors have lower credibility, especially for highly levered banks. Less credible supervisors (facing higher cost of intervention) end up intervening more banks, yet producing higher forbearance and systemic costs of bank distress. Importantly, when public intervention capacity is constrained, private recapitalization decisions become strategic complements, leading to equilibria with extremely high forbearance and high systemic costs of bank failure.

  • [1909]

    Konstantin Büchel, Maximilian V. Ehrlich, Diego Puga, Elisabet Viladencans-Marsal

    Calling from the outside: The role of networks in residential mobility


    Using anonymised cellphone data, we study the role of social networks in residential mobility decisions. Individuals with few local contacts are more likely to change residence. Movers strongly prefer places with more of their contacts closeby. Contacts matter because proximity to them is itself valuable and increases the enjoyment of attractive locations. They also provide hard-to-find local information and reduce frictions, especially in home-search. Local contacts who left recently or are more central are particularly influential. As people age, proximity to family gains importance relative to friends.

  • [1910]

    Anatoli Segura, Javier Suarez

    Optimally Solving Banks' Legacy Problems


    We characterize policy interventions directed to minimize the cost to the deposit guarantee scheme and the taxpayers of banks with legacy problems. Non-performing loans (NPLs) with low and risky returns create a debt overhang that induces bank owners to forego profitable lending opportunities. NPL disposal requirements can restore the incentives to undertake new lending but, as they force bank owners to absorb losses, can also make them prefer the bank being resolved. For severe legacy problems, combining NPL disposal requirements with positive transfers is optimal and involves no conflict between minimizing the cost to the authority and maximizing overall surplus.

  • [1911]

    Felipe Carozzi, Davide Cipullo, Luca Repetto

    Divided They Fall. Fragmented Parliaments and Government Stability


    This paper studies how political fragmentation affects government stability. Exploiting variation in the number of parties induced by a 5% vote share entry threshold in Spanish local councils, we show that the entry of an additional party in Parliament increases the probability of unseating the incumbent by 4 percentage points. We also document that mayors with more resources at their disposal for legislative bargaining are half as likely to be unseated. Challengers are younger, better educated, and more likely to win the following elections, suggesting that instability may induce positive selection on politicians. We interpret our results in light of a two-period bargaining model of coalition formation featuring government instability.


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