Economic analysis and research

Each year, nearly 200,000 abused and neglected children are placed into foster care in the U.S., yet the causal impacts of this policy are not fully understood. Using administrative data, we find that out-of-home placements result in significant increases in the test scores and decrease the likelihood of grade repetition of young girls (removed before the age of six). We do not find detectable impacts in young boys. Our findings suggest that removal impacts are particular to gender. 

Central bank liquidity lines gained momentum since the global financial crisis and were used extensively throughout the pandemic. US dollar swap lines are well studied, but much less is known about the effects of liquidity lines in euros. Do ECB euro liquidity lines decrease Euro funding costs in the targeted economies? And are there positive spillbacks for the Euro Area Economies? Our paper answers these questions by studying the direct and indirect effects of ECB liquidity lines. We use a difference-in-differences strategy to show that the announcement of ECB euro liquidity lines has a direct positive signalling effect since the premium paid by foreign agents to borrow euros in FX markets decreases up to 76 basis points relative to currencies not covered by these facilities. Additionally, the paper provides suggestive evidence that these facilities generate positive spillbacks to the euro area since domestic bank equity prices increase by 6.7% in euro area countries highly exposed via banking linkages to countries whose currencies are targeted by liquidity lines. 

This paper analyses the contribution of import competition to the regional divergence among US metropolitan areas over recent decades. It documents that the sharp rise in imports of Chinese manufacturing goods had a significant effect on the spatial skill polarisation and the divergence of college wage premium among local labor markets. The effects of the China trade shock were systematically different depending on the skill intensity of local services. Among regions with skill-intensive services, a higher exposure to import competition in manufacturing increased the number and wages of college-educated workers. The negative effects of the China shock concentrated in exposed regions with a low density of college-educated workers. The heterogeneous effects of import competition explain one third of the spatial skill polarisation and one fourth of the divergence in college wage premium. It is shown that the contribution of the trade shock operates through the reallocation of workers across sectors and regions. Using a novel measure of ‘labor market exposure’ to the China shock,  the author shows that service industries expand when local manufacturers face import competition. High human capital regions exposed to the China shock undergo a faster transition from manufacturing to skill-intensive service industries and attract college-educated workers from other locations.

We explore the heterogeneity across firms in the impact of and response to the COVID-19 shock using a survey conducted in November 2020 matched to balance-sheet information on firm characteristics. According to our results, the impact of the COVID-19 shock was larger in the case of small, young and less productive firms located in urban areas. Moreover, these firms resorted relatively more to public-guaranteed loans, tax deferrals, and furlough schemes (ERTEs). More indebted companies, which were not hit relatively harder by the shock, also perceived public-guaranteed loans as very useful. Firms consider that uncertainty represents a key hindrance to the recovery while the announcement of the effectiveness of the Pfizer vaccine on November 9th 2020 increased significantly firms' subjective recovery expectations. 

Even though the Fed does not have an explicit financial stability objective extending beyond its supervisory responsibilities, the public speeches of Fed officials, during the period 1997 to 2013, reveal that a higher speaking time or a higher negative tone on Financial Stability topics correlate with a more accommodative monetary policy stance. In contrast, communication on Housing topics correlates with a tighter policy stance. These results are mainly driven by the information in speeches of regional Fed presidents.

Spain has adopted 386,850 new norms since the beginning of the democratic period (1979-2020) and its rate of adoption has quadrupled since 1978 (12,250 new regulations were published in the year 2020). Notwithstanding, in addition to the problems that may arise from the "quantity” of regulations, the legal framework can also be complex due to “qualitative” reasons such as (1) the linguistic ambiguity of the norms or (2) their relational structure (i.e. references between legal documents). Our article innovates by analysing these new dimensions of complexity at the regional level using text mining and explores their relationship with productivity (as a relevant economic variable) and with judicial efficacy (as a relevant institutional-structural variable).

The Phillips curve has flattened out over the last decades. We develop a model that rationalizes this phenomenon as a result of the observed increase in polarization in many industries, a process along which a few top firms gain an increasing share of their industry market. In the model, firms compete à la Bertrand and there is exit and endogenous market entry, as well as optimal up and downgrading of technology. Firms with larger market shares find optimal to dampen the response of their price changes, thus cushioning the shocks to their marginal costs through endogenous countercyclical markups. Thus, regardless of its causes (technology, competition, barriers to entry, etc.), the recent increase in polarization in many industries emerges in the model as the key factor in explaining the muted responses of inflation to movements in the output gap witnessed recently.

We study the economic impact for financial institutions of using machine learning (ML) models in credit default prediction. We do so by using a unique and anonymized database from a major Spanish bank. We first measure the statistical performance in terms of predictive power, both in classification and calibration, comparing models like Logit and Lasso, with more advanced ones like Trees (CART), Random Forest, XGBoost and Deep Learning. We find that ML models outperforms traditional ones, although more complex ML algorithms do not necessarily predict better. We then translate this into economic impact by estimating the savings in regulatory capital that an institution could achieve when using a ML model instead of a simpler one to compute the risk-weighted assets following the Internal Ratings Based (IRB) approach. Our benchmark results show that implementing XGBoost instead of Lasso could yield savings from 12.4% to 17% in capital requirements, depending on the type of underlying assets.

We quantify the aggregate, distributional, and welfare consequences of setting an optimal progressivity level in the Spanish personal income tax scheme. For that purpose, we use a heterogeneous households general equilibrium model featuring both life cycle and dynastic elements which is calibrated to replicate some aggregate and distributional characteristics of the Spanish economy. The findings suggest that increasing progressivity would be optimal, even though it would involve an efficiency loss. The optimal reform of the tax schedule would reduce wealth and income inequality at the cost of negative effects on capital, labor, and output. The evaluation of these theoretical results with tax microdata describes a current scenario where the income-top households typically face suboptimal effective average tax rates.

We estimate the impact of air pollution on the incidence of sick leaves in a representative panel of employees affiliated to the Spanish social security system. Using over 100 million worker-by-week observations from the period 2005-2014, we obtain that higher air pollution increases the incidence of sick leaves, controlling for weather, individual effects, and a wide range of time-by-location controls. The effect is stronger for workers with pre-existing medical conditions, and weaker for workers with low job security. Our estimates are instrumental for quantifying air pollution damages due to changes in labor supply. Improved air quality in urban Spain between 2005 and 2014 saved at least €503 million in foregone production thanks to 5.55 million fewer worker absence days.​