Publications

We analyze monetary policy in a New Keynesian model with heterogeneous firms and financial frictions. Firms differ in their productivity and net worth and face collateral constraints that cause capital misallocation. TFP endogenously depends on the time-varying distribution of firms. Although a reduction in real rates increases misallocation in partial equilibrium, general-equilibrium effects overturn this result: a monetary expansion increases the investment of high-productivity firms relatively more than that of low-productivity ones, crowding out the latter and increasing TFP. We provide empirical evidence based on Spanish granular data supporting this mechanism. This has important implications for optimal monetary policy. We show how a central bank without pre-commitments engineers an unexpected monetary expansion to increase TFP in the medium run. In the event of a cost-push shock, the central bank leans with the wind to increase demand and reduce misallocation.

Target prices are an estimation of the future value of a company’s stock price. Although there is a general consensus about the importance of firm’s fundamentals when forecasting, there are also other determinants. This article sheds light on the effects of uncertainty, financial stress and volatility on target price estimations. To do so, different indicators are elaborated for the eight main Spanish financial entities from 1999 to 2020. They show that, on average, analysts have an optimistic bias in their valuations, and tend to react with a delay to stock movements. The different measures of uncertainty, financial stress and volatility affect their estimations a) fostering the optimistic bias, b) reducing the speed and c) willingness of the adjustment to share price movements, and d) make them trust less on stock prices as indicators of banks’ fundamentals. This effects are reinforced by the aggregation method of the composite target price (in particular the role of the older individual contributions). Both factors work in tandem: as the more uncertain the economic and financial environment is, the less likely aggregate target prices would move according to stock prices, because older individual contributions will slow the adjustment process. A simple change in the aggregation method reduces its impact on the indicators, without substantially altering their conclusions.

We develop a new method for estimating industry-level and aggregate total factor productivity (TFP) growth. Our method accounts for profits and adjustment costs, and uses firm surveys to proxy for changes in factor utilization. Using it to compute TFP growth rates in the United States and in five European countries since the early 1990s, we obtain results that substantially differ from the ones obtained with standard methods (i.e., Solow growth accounting and the utilization-adjusted method of Basu, Fernald, and Kimball, 2006). In every European country, our TFP series is less volatile and less cyclical than the standard ones, with striking differences during the Great Recession and Eurozone crisis. In the United States, our method indicates higher TFP growth overall and a more gradual productivity slowdown.

A number of central banks in advanced countries use ranges, or bands, around their inflation target to formulate their monetary policy strategy. The adoption of such ranges has been proposed by some policymakers in the context of the Fed and the ECB reviews of their strategies. Using a standard New Keynesian macroeconomic model, we analyze the consequences of tolerance range policies, characterized by a stronger reaction of the central bank to inflation when inflation lies outside the range, than when it is close to the target, i.e., the central value of the band. We show that (i) a tolerance band should not be a zone of inaction: the lack of reaction within the band endangers macroeconomic stability and leads to the possibility of multiple equilibria; (ii) the trade-off between the reaction needed outside the range versus inside appears unfavorable: a very strong reaction, when inflation is far from the target, is required to compensate for a moderately lower reaction within tolerance band; (iii) these results, obtained within the framework of a stylized model, are robust to many alterations, in particular allowing for the zero lower bound.

We examine linear correlation and tail dependence between market neutral hedge funds and the market portfolio conditional on the financial cycle. We document that the low correlation between these funds and the S&P 500 consists of a negative correlation during bear periods and a positive one during bull periods. In contrast, the remaining styles present a positive correlation across cycles. We also find that these funds present tail dependence only during bull periods. We study their implications for market timing and risk management.

During the long process of negotiation after the 2016 Brexit referendum there was a high
uncertainty about the final shape of bilateral trade relations between the European Union
(EU) and the United Kingdom (UK), especially for particular sectors and firms. Given
this context, the paper explores whether a fraction of Spanish trade with the UK was
diverted to other markets after the referendum as a function of Spanish firms’ exposition
to the British market. The paper shows that firms more exposed to that particular market
(above 10% of foreign sales and purchases) were able to almost fully divert the shock
in their sales and purchases, mostly to other European countries. Instead, there was
an heterogeneous responses of Spanish firms with a low share of British bilateral flows
over total trade. Given a particular share, trade diversion appears to be more limited for
imports relative to exports and for big companies.

This paper provides an accurate chronology of the Spanish reference business cycle by adapting the multiple change-point model proposed by Camacho, Gadea and Gómez Loscos (2021). In that approach, each individual pair of specific peaks and troughs from a set of indicators is viewed as a realization of a mixture of an unspecified number of separate bivariate Gaussian distributions, whose different means are the reference turning points and whose transitions are governed by a restricted Markov chain. In the empirical application, seven recessions in the period from 1970.2 to 2020.2 are identified, which are in high concordance with the timing of the turning point dates established by the Spanish Business Cycle Dating Committee (SBCDC).

Those of professional forecasters do. For a wide range of time series models for the euro area and its member states we find a higher average forecast accuracy of models that incorporate information on inflation expectations from the ECB’s SPF and Consensus Economics compared to their counterparts that do not. The gains in forecast accuracy from incorporating inflation expectations are typically not large but significant in some periods. Both short- and long-term expectations provide useful information. By contrast, incorporating expectations derived from financial market prices or those of firms and households does not lead to systematic improvements in forecast performance. Individual models we consider are typically better than univariate benchmarks but for the euro area the professional forecasters are more accurate, especially in recent years (not always for the countries). The analysis is undertaken for headline inflation and inflation excluding energy and food and both point and density forecast are evaluated using real-time data vintages over 2001-2019.

Empirical research suggests that lower interest rates induce banks to take higher risks. We assess analytically what this risk-taking channel implies for optimal monetary policy in a tractable New Keynesian model. We show that this channel creates a motive for the planner to stabilize the real rate. This objective conflicts with the standard inflation stabilization objective. Optimal policy thus tolerates more inflation volatility. An inertial Taylor-type reaction function becomes optimal. We then quantify the significance of the risk-taking channel for monetary policy in an estimated medium-scale extension of the model. Ignoring the channel when designing policy entails non-negligible welfare costs (0.7% lifetime consumption equivalent).

In this paper we use administrative data from the social security to study income dynamics and income risk inequality in Spain between 2005 and 2018. We construct individual measures of income risk as functions of past employment history, income, and demographics. Focusing on males, we document that income risk is highly unequal in Spain: more than half of the economy has close to perfect predictability of their income, while some face considerable uncertainty. Income risk is inversely related to income and age, and income risk inequality increases markedly in the recession. These findings are robust to a variety of specifications, including using neural networks for prediction and allowing for individual unobserved heterogeneity.

This paper empirically investigates the impact of local house price booms on capital misallocation within manufacturing industries. Using the geographic variation provided by the salient Spanish housing boom (2003-2007), we show that manufacturing firms exposed to positive local house price shocks received more credit from banks and their investment grew more intensively when they had a larger proportion of collateralizable real estate assets. We exploit the geographical variation in both house prices and pre-boom urban land supply at municipality level to document that this collateral channel was exacerbated for firms located in urban land-constrained geographical areas where real estate appreciation was larger. The interaction of geographical conditions, that led to heterogeneous housing booms, with the collateral channel on investment resulted in an increasing dispersion of the capital-labor ratio within industries. A simple counterfactual calculation suggests that the misallocation generated by the collateral channel on investment could account for between one-quarter and half of the fall in TFP experienced in the Spanish manufacturing sector over the housing boom.

In this paper, we develop a novel dataset of weekly economic conditions indices for the 50 U.S. states going back to 1987 based on mixed-frequency dynamic factor models with weekly, monthly, and quarterly variables that cover multiple dimensions of state economies. We show that there is considerable heterogeneity in the length, depth, and timing of business cycles across individual states. We assess the role of states in national recessions and propose an aggregate indicator that allows us to gauge the overall weakness of the U.S. economy. We also illustrate the usefulness of these state-level indices for quantifying the main forces contributing to the economic collapse caused by the COVID-19 pandemic and for evaluating the effectiveness of federal economic policies like the Paycheck Protection Program.

Polarization can have economic effects if the hostility between political camps (i.e., affective polarization) shapes economic expectations. This paper shows that, in polarized contexts, agents disagree more over their expectations, and that partisan hostility – rather than differences in individual economic circumstances or beliefs about government policies – drives this disagreement. The causal impact of partisanship is identied from the discontinuity created by shifts in Prime Ministers’ cabinet. The study of 134 shifts between 1993 and 2019 in 27 European countries reveals that left and right supporters with identical circumstances and information sets update their expectations in opposite directions, evidencing a partisan bias. Its size ranges from 1.5 to 0 standard deviations across these cabinet shifts. The polarization of parties – measured by their left-right positions or their cooperation within coalitions – explains half this variation, and adverse economic conditions amplify it. The analysis points to affective polarization (rather than disagreements over the likely effects of government policy) as the driver of partisan bias. Partisan bias extends to variables unaffected by future policy and, even when parties have similar economic positions, bias increases with polarization on non-economic dimensions. Overall, these findings suggest that political conflicts originally unrelated to economic matters could affect household behavior and policy debates and extend to the economic sphere.

Using Spanish confidential supervisory data, this paper examines the effect of geographic and business complexity, their interaction and relative importance for banks’ risk, where the degree of complexity stems from the corporate structure of banking groups affiliates. The results show that while business complexity results in higher risk, geographic complexity gives rise to diversification benefits, thus lowering risk. However, geographic complexity alone is not enough, as its effect depends on how it interacts with business complexity. Higher business complexity abroad in relation to that at home may counterbalance the benefits of diversification. In the same vein, focusing abroad on areas in which the group does not have expertise at home also results in higher risk.

We document that overcollateralisation of banks’ secured liabilities is positively associated with the risk premium on their unsecured funding. We rationalize this finding in a theoretical model in which costs of asset encumbrance increase collateral haircuts and the endogenous risk of a liquidity-driven bank run. We then test the model’s predictions using a novel dataset on asset encumbrance of the European banks. Our empirical analysis demonstrates that banks with more costly asset encumbrance have higher rates of overcollateralisation and rely less on secured debt. Consistent with theory, the effects are stronger for banks that are likely to face higher fire-sales discounts. This evidence acts in favour of the hypothesis that asset encumbrance increases bank risk, although this relationship is rather heterogeneous.

We analyze the evolution and price implications of aggregate sectorial holdings of stocks, using detailed information on the universe of publicly traded stocks in the euro area. We document that: i) households’ (HH) direct holdings represent a higher fraction of total ownership in domestic bank stocks than in non-financial corporation (NFC) stocks; ii) HH holdings of stocks increase (decrease) following a decline (increase) in the stock price, especially for domestic bank stocks; and iii) an increase in domestic HH holdings is followed by future (persistent) increases in the price of NFC stocks, but not for bank stocks. Moreover, during equity issuances, an increase in the share of domestic HH holdings is followed by a future (persistent) decrease in the stock price of bank stocks, but not for NFC stocks. Our results are consistent with HH being liquidity providers in the stock market, and at the same time subject to negative information asymmetries. We argue that this latter effect is more prevalent in domestic bank stocks than in NFC given the close relationships between HH and banks.

Vaccines are thought to be the best available solution for controlling the ongoing SARS-CoV-2 pandemic. However, the emergence of vaccine-resistant strains may come too rapidly for current vaccine developments to alleviate the health, economic and social consequences of the pandemic. To quantify and characterize the risk of such a scenario, we created a SIR-derived model with initial stochastic dynamics of the vaccine-resistant strain to study the probability of its emergence and establishment. Using parameters realistically resembling SARS-CoV-2 transmission, we model a wave-like pattern of the pandemic and consider the impact of the rate of vaccination and the strength of non-pharmaceutical intervention measures on the probability of emergence of a resistant strain. As expected, we found that a fast rate of vaccination decreases the probability of emergence of a resistant strain. Counterintuitively, when a relaxation of non-pharmaceutical interventions happened at a time when most individuals of the population have already been vaccinated the probability of emergence of a resistant strain was greatly increased. Consequently, we show that a period of transmission reduction close to the end of the vaccination campaign can substantially reduce the probability of resistant strain establishment. These results, therefore, suggest the convenience of maintaining non-pharmaceutical interventions and prevention protocols throughout the entire vaccination period.

This paper estimates the volatility index term structure for the Spanish bank industry (SBVX) using the implied volatility of individual banks and assuming market correlation risk premium. This methodology enables calculating a volatility index for arbitrary (non-traded) portfolios. Using data from 2015 to 2021, we find that SBVX informs about the dynamics of bank returns beyond the standard market volatility index VIBEX, especially when bank returns are negative; and that one-year SBVX beats shorter maturities in explaining bank returns. On the other hand, positive bank returns relate to the dynamics of VIBEX just as much as SBVX, which aligns with the belief that a drop in global volatility (uncertainty) positively affects firm performance and, therefore, bank value projections. We find one-month SBVX better than VIBEX to forecast monthly bank returns volatility, regardless of the tenor we use to compute VIBEX. This paper provides empirical evidence that idiosyncratic implied volatility is just as significant, or even more than global volatility, to monitor current and future banks’ share price performance. We advise using SBVX term structure, short-term VIBEX, and market correlation risk premium to monitor uncertainty and returns in the banking sector and foresee periods of stress in this industry. Our results may be of great interest to those seeking to estimate the banking sector’s sensitivity to uncertainty, volatility, and risk.

This article analyzes the impact of the unconventional monetary policies (UMPs) of four major central banks (the Fed, ECB, BoE and BOJ) on the probability of future market crashes. We exploit the heterogeneity of different UMP actions to disentangle their influence on reducing the ex ante perception of extreme events (tail risks) using the information contained in risk-neutral densities from the most liquid stock index options. The empirical findings show that the announcement of UMPs reduces the risk-neutral probability of extreme events across various horizons and thresholds, supporting the hypothesis of the risk-taking channel. Interestingly, foreign UMP actions also prove to be significant variables affecting domestic tail risks, mainly at longer horizons. These results reveal a cross-border effect of foreign UMPs on domestic tail risks. Finally, the dynamics of the UMPs are captured by a structural model that confirms a transitory impact of UMPs on market tail risk perceptions.

This paper measures impacts of removing children from families investigated for abuse or neglect. We use removal tendencies of child protection investigators as an instrument. We focus on young children investigated before age six and find that removal significantly increases test scores and reduces grade repetition for girls. There are no detectable impacts for boys. This pattern of results does not appear to be driven by heterogeneity in pre-removal characteristics, foster placements, or the type of schools attended after removal. The results are consistent with the hypothesis that development of abused and neglected girls is more responsive to home removal.

The use of central bank liquidity lines has gained momentum since the global financial crisis in order to provide liquidity in foreign exchange markets, while at the same time preventing threats to financial stability and negative spillbacks. US dollar swap lines are well studied, but much less is known about the effects of liquidity lines in euros. 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.

The use of quantitative tools to analyse the huge amount of qualitative information has been acquiring increasing importance. Market participants and, of course, Central Banks have been involved in this trend. The vast majority of qualitative data can be qualified as non-structured and refers mainly to news, reports or another kind of texts. Its transformation into structured data can improve the availability of information and hence, decision making. This article applies sentiment analysis tools to text data in order to quantify the impact of Covid-19 on the analysts’ opinions. Using this methodology, it is possible to transform qualitative non-structured data into a quantitative index that can be used to compare reports from different periods and countries. The results show the pandemic worsens banking sentiment in Europe, which coincides with higher uncertainty in the stock market. There are also regional differences in the decline in sentiment as well as higher divergence is observed across opinions.

“Awareness” about the occurrence of viral infectious (or other) tail risks can influence their socioeconomic inter-temporal impacts. A branch of the literature finds that prior lifetime exposure to signicant shocks can affect people and societies, i.e. by changing their perceived probability about the occurrence of an extreme, negative shock in the future. In this paper we proxy “awareness” by historical exposure of a country to epidemics, and other catastrophic events. We show that in a large cross-section of more tan 150 countries, more “aware” societies suffered a less intense impact of the COVID-19 disease, in terms of loss of lives and, to some extent, economic damage.

This study revisits the trade and welfare effects of 19th century bilateralism exploiting the latest developments in structural gravity models, including the consideration of domestic trade. Using bilateral trade data between 1855 and 1875, I show that the Cobden-Chevalier network, i.e. a system of bilateral trade agreements including the Most Favored Nation clause, had large, positive and significant effects on members’ trade. These, however, were heterogeneous at the treaty-level. I then calculate its general equilibrium effects on total trade and welfare. They are considerable, while trade diversion effects are negligible. These results reshape the understanding of the Cobden-Chevalier network, helping in further rationalizing the “free trade epidemic” of the 1860s and 1870s.

This paper investigates the impact of trade protectionism in the form of tariff barriers on Spanish goods exports. The Spanish economy has signicantly increased its degree of openness, which improves potential economic growth, but also implies a higher exposure to the protectionist shift in the international environment observed in the last years. With the purpose of assessing exports sensitivity to tariff increases, we obtain a database combining annual tariffs applied to Spanish products over the years 1995-2019 from WITS and bilateral extra-EU Spanish goods exports from Eurostat, with a product disaggregation level at 6 digits. We estimate the effect of tariffs both on exporting probability (i.e. exports extensive margin) through a linear probability model and exports levels (i.e. exports intensive margin) through a gravity equation. The findings of this paper show that higher tariffs reduce exports levels through extensive an intensive margins. A 1% tariff increase reduces on average the probability of exporting to aspecic market by nearly 0.08 pp. and exported values by around 1%.

This paper explores the heterogeneity across firms within each sector and region in the impact of and response to the COVID-19 shock. It relies on a survey conducted by Banco de España to 4,004 companies in November 2020 matched to very rich 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 within each sector-region pair. 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, but observable characteristics do not explain the variation in the perception of uncertainty once the impact of the shock is accounted for. Finally, we use the announcement of the Pfizer vaccine on November 9th 2020 as a natural experiment to provide evidence that the vaccine announcement increased significantly firms’ subjective recovery expectations.

The design of the key elements of a public budget-neutral environmental fiscal reform could have very different implications in terms of its environmental and macroeconomic impact. Our proposals rely on a carbon tax on fossil fuels covering all economic sectors. It would be a powerful and efficient instrument for reducing emissions, as it gives economic agents an incentive to find ways to save energy and switch to greener energy sources while generating significant tax revenues whose judicious use may have positive macroeconomic effects. In addition, a carbon tax is easy to administer since it can be integrated into existing fuel excise duties. We build a novel model to assess the environmental and economic impact of a set of environmental fiscal reforms in Spain which are defined by different levels of the carbon tax, the possibility of a border carbon adjustment and alternative uses of the tax revenues generated. In this framework, we incorporate technological innovation, which will allow firms to produce with non-polluting inputs and, specifically, the electricity sector, to increase the role of renewables in its generation mix. The results indicate that carbon tax designs with border carbon adjustment tend to be more effective in lowering emissions in Spain. They also suggest that an appropriately designed environmental fiscal reform may even boost economic activity in the medium term if the revenues are used to reduce other, more distorting taxes.

We examine the contribution of economic and institutional transitions as two potential sources of subnational economic growth in Spain. To this end, we exploit the economic reforms of the 1959 Stabilization Plan (as an example of technocratic, economy-oriented reform) and the democratic transition in 1979 in Spain as the sources of variation for a sample of 50 Spanish provinces in the period 1950-2016. Our approach is to examine the impacts by estimating the missing counterfactual scenarios using the synthetic control method. Our results unveil a positive effect for both economic and institutional transitions on subnational economic growth. A direct comparison of both transitions suggests that the effect of economic liberalization is four-fold higher than the effect of political liberalization. The average growth effect of the economic liberalization is around 40% higher relative to the counterfactual scenario and it appears to be permanent. The estimated effects are robust to the variety of placebo tests and additional robustness checks. This article also deepens the analysis of the effects of the 1959 plan and finds that the policies that generated the most positive impact were those of an “internal” nature, compared to the external ones, dependent on access to the IMF (also positive, but of lesser impact).

Economic theory suggests including domestic trade flows when estimating structural gravity models. The inclusion of domestic trade flows helps to identify parameters that cannot be estimated with international trade flows alone. The complication is that domestic trade flows can be measured empirically in different ways. Does it matter which one is used? We compare the three most common approaches to measuring domestic trade and show that they lead to very similar estimates of the parameters that are usually estimated within a structural gravity framework.

Using an estimated life-cycle model, we quantify the role of heterogeneity in wealth returns for the response of income to marginal tax changes. In our economy, agents who are sufficiently productive can obtain higher returns by choosing to be entrepreneurs. Return heterogeneity amplifies the responsiveness of total income to marginal tax changes along the entire income distribution with the top 1 percent displaying the highest elasticities. Return heterogeneity increases the incentives to invest for the richest, highreturn entrepreneurs, thus amplifying their income responses to marginal tax changes. This reallocation of capital increases aggregate productivity, generating a larger boost in equilibrium wages. This in turn strengthens the income response of the bottom 90 percent, but nevertheless, their response is smaller than at the top.

This paper analyzes the contribution of import competition to the regional divergence among US metropolitan areas over recent decades. I document that the sharp rise in imports of Chinese manufacturing goods had a significant effect on the spatial skill polarization 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 polarization and one fourth of the divergence in college wage premium. I show 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”, I document 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 estimate the impact of MERCOSUR on trade flows and on gains from trade for its member countries using a standard modern general equilibrium quantitative structural gravity model. We find a highly heterogeneous impact on bilateral trade flows and gains from trade. We estimate that gains from trade attributable to MERCOSUR are equivalent to a 4.0 % increase in per-capita consumption for Argentina. For the other countries, gains from trade are smaller: 0.8 % for Uruguay, 0.5 % for Paraguay, and 0.3 % for Brazil. We study whether Brazil would benefit from withdrawing from MERCOSUR and signing a trade agreement with a different trade bloc but conclude that net gains from such a switch would be small, if any.

The added worker effect (AWE) measures the entry of individuals into the labor force due to their partners’ adverse labor market outcomes. We propose a new method to calculate the AWE that allows us to estimate its effect on any labor market outcome. The AWE reduces the fraction of households with two non-employed members by 16% for the 1977-2018 period; 28% in the 1990 recession and 23% during the great recession. The AWE also accounts for why women’s employment is much less cyclical and more symmetric than men’s. Without the AWE, married women’s employment would be as volatile as men and display negative skewness (declining quickly in recessions and recovering slowly in expansions). In recessions, while some women lose their employment, others enter the labor market and find jobs. This keeps female employment relatively stable.

In this paper we analyze the price setting behavior in Chile by using scraped data from public websites of the main retailers including supermarkets, a pharmacy retailer and car dealerships. The data collection started in July 2019 and the dataset covers two major recent events: (1) the social outbreak and (2) the state of emergency declaration due to Covid-19, both episodes led to disruptions in the economy. With information on product varieties that accounts for 22 % of the CPI basket, we document several empirical findings as regards price setting behaviour in terms of stickiness, that is, frequency, implied duration and the size of price adjustments. We find that in spite of facing large shocks, prices adjusted very little, at a lower frequency and at a smaller size than prior to these two events. We also find that there was a reduction on product variety availability on-line, a typical feature that also has been found during natural disasters such as earthquakes. The reduction in product availability poses additional difficulties to construct CPI indexes and to properly capture price rigidities, which are relevant for monetary policy.

We document systematic and signicant time variation in US lifecycle nondurable
consumption profiles. Consumption profiles have consistently become flatter:
intergenerational differences in consumption across age groups have decreased over
time. Pooling data across different periods to identify lifecycle profiles and failing to
account for unobserved heterogeneity masks relevant time variations and may articially
generate hump-shaped consumption age profiles. The main driver behind lifecycle
consumption variations are lifecycle income changes, which display similar flattening.
Employing a lifecycle model we show changes in income are sufficient to match the
movements in consumption.

This paper studies the informational content of speeches of Fed officials, focusing on financial stability, from 1997 to 2018. We construct indicators that measure the intensity and tone of this topic for both Governors and Fed presidents. When added to a standard forward-looking Taylor rule, a higher topic intensity or negative tone is associated with more monetary policy accommodation than implied by the state of the economy. Our results are mainly driven by the information in speeches of Fed presidents. We discuss several channels to rationalize this finding.

We estimate the effective reproduction number (Rt) of the current Covid-19 pandemic, with US daily infections data between February and September of 2020, at the county level. This is then used to estimate the effect of weather and mobility on the spread of the pandemic. We find a strong and significant effect of the weather: lower temperaturas are associated with a higher Rt, and this effect is bigger at temperatures below 0ºC. At low temperatures, precipitations are also associated with a higher Rt. We also find that mobility reductions related to certain types of locations (retail and recreation, transit stations, and workplaces) are effective at reducing Rt, but it is an increase of the time spent in parks that helps reduce the spread of the pandemic. The negative effect of increased general mobility is bigger in counties with higher population density, worse numeracy and literacy PIAAC scores, or a lower share of employment in the services sector. Quantitatively, our estimates imply that a 20ºC fall in temperatures from summer to winter would increase Rt by +0.35, which can be the difference between a wellcontrolled evolution and explosive behavior; and, if this can’t be neutralized through general improvements in the fight to stop the pandemic, the additional reduction in mobility that would be needed to compensate for this would be equivalent to returning, from the more relaxed levels observed in the summer, back to the strictest mobility reductions recorded in the US in April.

We introduce a new class of time-varying parameter vector autoregressions (TVP-VARs) where the identified structural innovations are allowed to influence the dynamics of the coefficients in these models. An estimation algorithm and a parametrization conducive to model comparison are also provided. We apply our framework to the US economy. Scenario analysis suggests that, once accounting for the influence of structural shocks on the autoregressive coefficients, the effects of monetary policy on economic activity are larger and more persistent than in an otherwise standard TVP-VAR. Our results also indicate that cost-push shocks play a prominent role in understanding historical changes in inflation-gap persistence.

Complex or poorly drafted regulations are more difficult for economic agents to implement, eroding economic efficiency. The literature has so far concentrated on the analysis of regulatory complexity as a phenomenon related to the “quantity” of norms. Regulation can also be complex because of “qualitative” reasons such as its linguistic ambiguity or its relational structure (references between legal documents). This article innovates by analyzing these new dimensions of complexity: we develop new indicators for legibility and regulatory interconnectedness. To do so, we constructed a new database (RECOS - Regulatory Complexity in Spain) extracting information from 8,171 norms (61 million words) covering the regulation set of all the Spanish autonomous regions. We analyze the relationship between these new indicators and productivity (as a relevant economic variable) and judicial efficacy (as a relevant institutional-structural variable). While each of these areas should be analyzed in separate articles, this research shows that the new dimensions of regulation complexity matter and also have significant results.

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.

In this paper we study the performance of several machine learning (ML) models for credit default prediction. We do so by using a unique and anonymized database from a major Spanish bank. We compare the statistical performance of a simple and traditionally used model like the Logistic Regression (Logit), with more advanced ones like Lasso penalized logistic regression, Classification And Regression Tree (CART), Random Forest, XGBoost and Deep Neural Networks. Following the process deployed for the supervisory validation of Internal Rating-Based (IRB) systems, we examine the benefits of using ML in terms of predictive power, both in classification and calibration. Running a simulation exercise for different sample sizes and number of features we are able to isolate the information advantage associated to the access to big amounts of data, and measure the ML model advantage. Despite the fact that ML models outperforms Logit both in classification and in calibration, more complex ML algorithms do not necessarily predict better. We then translate this statistical performance into economic impact. We do so by estimating the savings in regulatory capital when using ML models instead of a simpler model like Lasso to compute the risk-weighted assets. Our benchmark results show that implementing XGBoost could yield savings from 12.4% to 17% in terms of regulatory capital requirements under the IRB approach. This leads us to conclude that the potential benefits in economic terms for the institutions would be significant and this justify further research to better understand all the risks embedded in ML models.

Spain is on a path towards the decarbonization of the economy. This is mainly due to structural changes in the economy, where less energy-intensive sectors are gaining more relevance, and due to a higher use of less carbon-intensive primary energy products. This decarbonization trend is in fact more accentuated than that observed in the EU28, but there is still much to be done in order to reverse the huge increases in emissions that occurred in Spain prior to the 2007 crisis. The technical energy efficiency is improving in the Spanish economy at a higher rate than in the EU28, although all these gains are offset by the losses that the country suffers due to the inefficient use of the energy equipment. There is an installed energy infrastructure (in the energy-consumer side) in the Spanish economy that is not working at its maximum rated capacity, but which has very high fixed energy costs that reduce the observed energy efficiency and puts at risk the achievement of the emissions and energy consumption targets set by the European institutions. We arrive to these findings by developing a hybrid decomposition approach called «input-output logarithmic mean Divisia index» (IO-LMDI) decomposition method. With this methodological approach, we can provide an allocation diagram scheme for assigning the responsibility of primary energy requirements and carbon-dioxide emissions to the end-use sectors, including both economic and non-productive sectors. In addition, we analyze more potential influencing factors than those typically examined, we proceed in a way that reconciles energy intensity and energy efficiency metrics, and we are able to distinguish between technical and observed end-use energy efficiency taking into account potential rebound effects and other factors.

Sovereign spreads within the European Monetary Union (EMU) arise because markets price-in heterogeneous country fundamentals, but also re-denomination risks, given the incomplete nature of EMU. This creates a permanent risk of financial fragmentation within the area. In this paper we claim that political decisions that signal commitment to safeguarding the adequate functioning of the euro area influence investors’ valuations. We focus on decisions conducive to enhancing the institutional framework of the euro area (“EMU deepening”). To test our hypothesis we build a comprehensive narrative of events (decisions) from all documents and press releases issued by the Council of the EU and the European Council during the period January 2010 to March 2020. We categorize the events as dealing with: (i) economic and financial integration; (ii) fiscal policy; (iii) bailouts. With our extremely rich narrative at hand, we conduct event-study regressions with daily data to assess the impact of events on sovereign bond yields and find that indeed decisions on financial integration drive down periphery spreads. Moreover, while decisions on key subjects present a robust effect, this is not the case with prior discussions on those subjects at the Council level. Finally, we show that the impacts arise from reductions in peripheral sovereign spreads, and not by the opposite movement in core countries. We conclude that EU policy-makers have at their disposal signicant “political space” to reduce fragmentation and gain “policy space”.

This article exploits two newspaper archives to track economic policy uncertainty in Spain in 1905-1945, a period of extreme political polarization. We find that the outbreak of the civil war in 1936 was anticipated by a striking upward level shift of uncertainty in both newspapers. We study the dynamics behind this shift and provide evidence of a strong empirical link between increasing uncertainty and the rise of divisive political issues at the time: socio-economic conflict, regional separatism, power of the military, and role of the church. This holds even when we exploit variation in content at the newspaper level.

Is the Spanish economy positioned at its optimal progressivity level in personal income tax? This article quantifies the aggregate, distributional, and welfare consequences of moving towards such an optimal level. A heterogeneous households general equilibrium model featuring both life cycle and dynastic elements is calibrated to replicate some characteristics of the Spanish economy and used to evaluate potential reforms of the tax system. 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. Finally, these theoretical results are evaluated using tax micro data and describe a current scenario where the income-top households typically face suboptimal effective average tax rates.