Publications

Can the Spanish government generate more tax revenue by making personal income taxes more progressive? To answer this question, we build a life-cycle economy with uninsurable labor productivity risk and endogenous labor supply. Individuals face progressive taxes on labor and capital incomes and proportional taxes that capture social security, corporate income, and consumption taxes. Our answer is yes, but not much. A reform that increases labor income taxes for individuals who earn more than the mean labor income and reduces taxes for those who earn less than the mean labor income generates a small additional revenue. The revenue from labor income taxes is maximized at an effective marginal tax rate of 51.6% (38.9%) for the richest 1% (5%) of individuals, versus 46.3% (34.7%) in the benchmark economy. The increase in revenue from labor income taxes is only 0.82%, while the total tax revenue declines by 1.55%. The higher progressivity is associated with lower aggregate labor supply and capital. As a result, the government collects higher taxes from a smaller economy. The total tax revenue is higher if marginal taxes are raised only for the top earners.The increase, however, must be substantial and cover a large segment of top earners. The rise in tax collection from a 3 percentage points increase on the top 1% is just 0.09%. A 10 percentage points increase on the top 10% of earners (those who earn more than €41,699) raises total tax revenue by 2.81%.

The aim of this paper is to construct a text-based indicator that reflects the sentiment of the Banco de España economic outlook reports. Our sentiment indicator mimics very closely the first release of the GDP growth rate, which is published after the publication of the reports, and the Banco de España quarterly forecasts of the GDP growth rate. This means that the qualitative narrative contained in the reports contains similar information to the one conveyed by the quantitative forecasts. In addition, the narrative complements the quantitative projections by discussing information which is not directly reflected in the point forecasts.

We estimate the causal 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 estimate the relationship between the share of days an individual is on sick leave in a given week and exposure to particulate matter (PM10) at the place of residence, controlling for weather, individual effects, and a wide range of time-by-location controls. We exploit quasi-experimental variation in PM10 that is due to Sahara dust advection in order to instrument for local PM10 concentrations. We estimate that the causal effect of PM10 on sick leaves is positive and varies with respect to worker and job characteristics. 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. We estimate that improved ambient air quality in urban Spain between 2005 and 2014 saved at least €503 million in foregone production by reducing worker absence by more than 5.55 million days.

We show strong overall and heterogeneous economic incidence effects, as well as distortionary effects, of only shifting statutory incidence (i.e., the agent on which taxes are levied), without any tax rate change. For identification, we exploit a tax change and administrative data from the credit market: (i) a policy change in 2018 in Spain shifting an existing mortgage tax from being levied on borrowers to being levied on banks; (ii) some areas, for historical reasons, were exempt from paying this tax (or have different tax rates); and (iii) an exhaustive matched credit register. We find the following robust results: First, after the policy change, the average mortgage rate increases consistently with a strong – but not complete – tax pass-through. Second, there is a large heterogeneity in such pass-through: larger for borrowers with lower income, a smaller number of lending relationships, not working for the lender, or facing less banks in their zip-code, thereby suggesting a bargaining power mechanism at work. Third, despite no variation in the tax rate, and consistent with the non-full tax pass-through, the tax shift increases banks’ risk-taking. More affected banks reduce costly mortgage insurance in case of loan default (especially so if banks have weaker ex-ante balance sheets) and expand into non-affected but (much) ex-ante riskier consumer lending, experiencing even higher ex-post defaults within consumer loans.

We use the latest available empirical evidence on the impact of the COVID-19 shock on the EU economy to predict its effect on firm entry, and in particular on high-growth startups, and on the related short- and long-run impact on employment growth. We find that the COVID-19 shock is expected to reduce firm entry and that its overall impact is very sensitive to financial conditions. A relatively small increase in financial frictions is likely to strongly reduce the entry of high-growth startups, with fewer jobs created in the short run but, more importantly, also slower employment growth in the long run. We then develop a model with heterogeneous startup types and simulate the effects of the COVID-19 shock on the entry and growth of a cohort of new firms to evaluate alternative policies. We find that a loan subsidy that reduces the excess cost of credit for new startups is the most efficient policy in promoting the entry of high-growth startups. The comparison of this subsidy with a wage subsidy that supports current employment shows that, for the same overall costs, the number of jobs created by the loan subsidy in the long term is significantly larger than that created by the wage subsidy in the short term. Our findings imply that, while policies aiming to stimulate current employment are important, in order to ensure also a faster recovery in the future they should be accompanied by measures directed at reducing the cost of credit for new businesses.

We explore the cognitive skill gap between the adult population in Spain and in the rest of European Union countries using the Programme for the International Assessment of Adult Competencies. We find that differences in schooling account for about a third of the average difference in cognitive test scores, whereas differences in socio-economic background explain about one fourth of the average score gap. While cognitive skill gaps are increasing along the distribution of test scores, differences in educational stocks and socio-economic factors explain a larger fraction of the gap at the bottom than at the top of the skill distribution.

We show that loan origination time is key for bank lending standards, cycles, defaults and failures. We exploit the credit register from Spain, with the time of a loan application and its granting. When VIX is lower (booms), banks shorten loan origination time, especially to riskier firms. Bank incentives (capital and competition), capacity constraints, and borrower-lender information asymmetries are key mechanisms driving results. Moreover, shorter (loan-level) origination time is associated with higher ex-post defaults, also using variation from holidays. Finally, shorter precrisis origination time —more than other lending conditions— is associated with more bank-level failures in crises, consistent with lower screening.

In several OECD countries employer federations and unions fix skill-specific wage floors for all workers in an industry. One view of those “explicit” contracts argues that the prevailing wage structure reflects the labor market conditions back at the time when those contracts were bargained, with little space for renegotiation. An alternative view stresses that only workers close to the minima are affected by wage floors and that the wage structure reacts to current labor market conditions. We disentangle both models using a novel data set that combines more than 1,000 signature dates and 15,000 wage floors set in the metal working industry with labor market histories of metal workers drawn from Social Security records in Italy and Spain. An increase in the contemporaneous local unemployment rate of 1 p.p. diminished contemporaneous mean wages by about 0.45 p.p. between 2005 and 2013 in both countries. Instead, a 1 p.p. higher unemployment rate back at the time of contract renewal reduced wages by 0.7 p.p., an impact driven by wages close to the negotiated wage floors. Even though the evidence for earlier periods is mixed in Italy, the results do not support the view that the wage structure reflects labor market conditions at the time of bargaining. The results support the hypothesis that (most) wages respond to local current unemployment rate, although the estimated elasticity falls short of the prediction of an off-the-shelf bargaining model.

In this article we apply text mining techniques to analyse the TCFD recommendations on climate-related disclosures of the 12 significant Spanish financial institutions using publicly available corporate reports from 2014 until 2019. In our analysis, applying our domain knowledge, first we create a taxonomy of concepts present in disclosures associated with each of the four areas described in the TCFD recommendations. This taxonomy is then linked together by a set of rules in query form of selected concepts. The queries are crafted so that they identify the excerpts most likely to relate to each of the TCFD’s 11 recommended disclosures. By applying these rules we estimate a TCFD compliance index for each of the four main areas for the period 2014-2019 using corporate reports in Spanish. We also describe some challenges in analysing climate-related disclosures. The index gives an overview of the evolution of the level of climate-related financial disclosures present in the corporate reports of the Spanish banking sector. The results indicate that the quantity of climate-related disclosures reported by the banking sector is growing each year. Besides, our study also suggests that some disclosures are only present in reports different than annual and ESG reports, such as Pillar 3 reports or reports on remuneration of directors.

To analyze the international transmission of business cycle fluctuations, we propose a new multilevel dynamic factor model with a block structure that (i) does not restrict the factors to being orthogonal and (ii) mixes data sampled at quarterly and monthly frequencies. By means of Monte Carlo simulations, we show the high performance of the model in computing inferences of the unobserved factors, accounting for the spillover effects, and estimating the model’s parameters. We apply our proposal to data from the G7 economies by analyzing the responses of national factors to shocks in foreign factors and by quantifying the changes in national GDP expectations in response to unexpected positive changes in foreign GDPs. Although the share of the world factor as a source of the international transmission of fluctuations is still signicant, this is partially absorbed by the spillover transmissions. In addition, we document a pro-cyclical channel of international transmission of output growth expectations, with the US and UK being the countries that generate the greatest spillovers and Germany and Japan being the countries that generate the smallest spillovers. Therefore, policymakers should closely monitor the evolution of foreign business cycle expectations.

A recent literature documents a secular increase in the sales-weighted markups in the United States, a phenomenon that was driven by large and productive firms at the top of the profit distribution. Using rich balance-sheet data, this paper documents the behavior of markups in Spain before, during, and in the aftermath of the Great Recession. We document that markups rose during the financial crisis. Unlike in the U.S., these dynamics were led by small firms: in response to a drop in sales, these firms were unable to increase their productive efficiency when average costs increased. As a consequence, and in order to escape a sharp decline in profit rates, they increased their markups. Simultaneously, large firms were able to increase efficiency, and their markups remained relatively constant. We argue that the increase of relative markups by small firms came at the expense of losing market share, which in the very short run proved to be preferred than exiting the market.

New reports show that the financial sector is increasingly adopting machine learning (ML) tools to manage credit risk. In this environment, supervisors face the challenge of allowing credit institutions to benefit from technological progress and financial innovation, while at the same ensuring compatibility with regulatory requirements and that technological neutrality is observed. We propose a new framework for supervisors to measure the costs and benefits of evaluating ML models, aiming to shed more light on this technology’s alignment with the regulation. We follow three steps. First, we identify the benefits by reviewing the literature. We observe that ML delivers predictive gains of up to 20 % in default classification compared with traditional statistical models. Second, we use the process for validating internal ratings-based (IRB) systems for regulatory capital to detect ML’s limitations in credit risk mangement. We identify up to 13 factors that might constitute a supervisory cost. Finally, we propose a methodology for evaluating these costs. For illustrative purposes, we compute the benefits by estimating the predictive gains of six ML models using a public database on credit default. We then calculate a supervisory cost function through a scorecard in which we assign weights to each factor for each ML model, based on how the model is used by the financial institution and the supervisor’s risk tolerance. From a supervisory standpoint,having a structured methodology for assessing ML models could increase transparency and remove an obstacle to innovation in the financial industry.

In their seminal article, Guiso et al. (2008) uncover a positive relationship between several measures of gender equality and the math gender gap (which tends to favor boys) by exploiting cross-sectional variation in PISA test scores from 39 countries – the majority of which belong to the OECD – at a given year (2003). Using five waves of PISA data spanning the period 2003-2015 and exploiting variation both across – and within – countries, we find that the positive association between the female-male gender gap in math test scores and several measures of gender equality vanishes in OECD countries once we account for country fixed effects. Interestingly, our analysis also uncovers a positive and statistically significant association between the math gender gap and several gender equality indicators for countries in the bottom quartile of per capita GDP. This association is robust to controlling for country-level time-invariant unobserved heterogeneity.

This paper extends a model of firm dynamics to incorporate heterogeneous privately held and publicly traded firms facing different financial frictions, and the decision to become publicly traded (Initial Public Offering, or IPO) is endogenous. This allows changes in the economic environment to affect these firms differently, impacting the selection into becoming publicly traded, and its macroeconomic outcomes. Firms are born privately held and small due to financial frictions. They finance investment with internal resources and debt and have the choice to go public (IPO). The main trade-off is access to external equity financing, at a one-off cost of IPO and an increased cost of operation. The calibrated model is successful in capturing the size distribution of firms, the share of publicly traded firms, and the dynamics around the IPO date. The decrease in corporate and dividend taxes experienced from the 1970s to the 1990s benefited more publicly traded firms financing with equity at the margin. This helps explaining the stock market boom, and the observed changes in the characteristics of firms going public, their investment and payout behavior. I perform some counterfactual exercises to understand what could be the reasons behind the decrease in publicly traded firms since the 2000s: increased cost of being public, increased access to debt, or changes in the idiosyncratic shock process. I find these changes are consistent with part (though not all) of the changes in IPO choice, payout and investment behavior of publicly traded firms in this period.

The paper reviews the economic risks associated with regimes of high public debt through
DSGE model simulations. The large public debt build-up following the 2009 global
financial and economic crisis acted as a shock absorber for output, while in the recent
and more severe COVID19-crisis, an increase in public debt is even more justified given
the nature of the crisis. Yet, once the crisis is over and the recovery firmly sets in, keeping
debt at high levels over the medium term is a source of vulnerability in itself. Moreover,
in the euro area, where monetary policy focuses on the area-wide aggregate, countries
with high levels of indebtedness are poorly equipped to withstand future asymmetric
shocks. Using three large scale DSGE models, the simulation results suggest that highdebt
economies (1) can lose more output in a crisis, (2) may spend more time at the zerolower
bound, (3) are more heavily affected by spillover effects, (4) face a crowding out of
private debt in the short and long run, (5) have less scope for counter-cyclical fiscal policy
and (6) are adversely affected in terms of potential (long-term) output, with a significant
impairment in case of large sovereign risk premia reaction and use of most distortionary
type of taxation to finance the additional debt burden in the future. Going forward, reforms
at national level, together with currently planned reforms at the EU level, need to be
timely implemented to ensure both risk reduction and risk sharing and to enable high debt
economies address their vulnerabilities.

We exploit the GEOSTAT 2011 population grid with a very high 1-km2 resolution to
document that Spain presents the lowest density of settlements among European
countries. We uncover that this anomaly cannot be accounted for by adverse geographic
and climatic conditions. Using techniques from spatial econometrics, we identify the
clusters that exhibit the lowest densities within Spain after controlling for geo-climatic
factors: these areas mainly belong to Teruel, Zaragoza, Ciudad Real, Albacete, Sevilla
and Asturias. We also explore the attributes that characterize the municipalities located
in these low-density areas: larger population losses during the 1950-1991 rural exodus,
higher shares of local-born inhabitants, longer distances to the province capital, higher
shares of population employed in agriculture, and larger increases in regionalist vote
after the Great Recession.

We construct a new newspaper-based sentiment indicator for Spain that allows us to
monitor Spanish economic activity in real-time. As opposed to the traditional surveybased
confidence indicators that are released at the end of the month, our indicator can
be constructed on a daily basis and updated in real-time. We compare our proposed
index with the popular Economic Sentiment Indicator of the European Commission,
and we show that ours performs significantly better in nowcasting the Spanish GDP.
In addition, our indicator proves to be helpful in order to predict the current COVID-19
recession from an earlier date. All in all, our indicator performs similarly to or even
outperforms other soft indicators, with the advantage of being updated daily. Thus, it
provides a valuable option when measuring the confidence in the economy.

The recent release of EUREGIO, a novel global input-output database with regional
detail for EU countries, allows to analyze the participation of EU regions in Global Value
Chains and their implications for the propagation of sector-specific shocks. We focus on
Spanish regions to exploit the granular information embedded in this database. We first
characterize foreign and domestic trade inter-linkages of Spanish regions and sectors.
Using an extended version of the Leontief scheme, we compute upstream output and
value added multipliers. Then, we calculate indicators developed in the Global Value
Chain literature to breakdown each region trade flows, both exports and outflows,
into value added components. Finally, by means of examples, we analyze the role of
networks (domestic or foreign) in the propagation of demand shocks (from customers
to suppliers), to evaluate the heterogeneous impact across regions and to illustrate
the potential of this approach. Our findings indicate that Spanish regions participate
differently in Global Value Chains and this fact may have important implications in the
propagation of shocks. According with our results, the strongest user-supplier linkages
are usually within the same sector, and, in general, with industries within the same
region or other Spanish regions. The Basque Country is the region with sectors with
the largest total output-multipliers and Catalonia with the lowest ones. Concerning
their participation in Global Value Chains, the Basque Country is the most integrated
region in the backward segment of the value chain, closely followed by Madrid, while
Catalonia –and a lesser extent Canary Islands– shows a comparatively low participation.
Concerning the forward participation, Catalonia shows the largest one on exports, while
Madrid and the Basque Country in outflows.

Public investment in advanced economies is at historical lows, and shows a declining
trend since at least the 1980s. Two main hypotheses have been posed to rationalize this
fact. On the one hand, the “social dominance hypothesis” claims that this is related to
structural factors, given the upward social expenditure trends related to ageing populations
and social preferences, and the operation of the government budget constraint (limits
to further increase significantly tax revenues and public debt, in a context of secular
stagnation). On the other hand, another branch of the literature indicates that too-rigid
fiscal rule frameworks cause fiscal retrenchment episodes to hinge heavily on public capital
expenditure, which does not recover enough in the subsequent expansion, creating a sort
of downward hysteresis behaviour in this budgetary item. In this paper we look jointly at
both sets of duelling explanatory factors, and show that both are key to understanding
public investment dynamics in advanced economies over the past decades.

We construct Economic Policy Uncertainty (EPU) indexes for a number of Latin American
(LA) economies (Argentina, Brazil, Chile, Colombia, Mexico, Peru, Venezuela) and the
region as a whole based on the Spanish press. Our measures are comparable across
countries. We study the macroeconomic effects of LA EPU shocks on the analyzed
American economies and the Spanish economy. To study the international spillover
effects on the Spanish economy we carry out two exercises by means of vector
autoregression models. First, we estimate responses to unexpected shocks in LA EPU
of the quotations of Spanish companies which are highly exposed to Latin America.
Second, we study the impact of LA EPU shocks on Spanish macroeconomic aggregates.
Unexpected shocks in LA EPU dampen signicantly the commercial relationship between
Spain and LA countries. Spanish firms decrease their exports and foreign direct
investments towards LA countries that experience negative shocks in EPU.

In this paper we analyze the EU-Mercosur agreement and predict its effects on trade and
welfare using a general equilibrium structural gravity model. First, we exploit the detailed
provision-level information available for the EU-Mercosur agreement to identify partial
equilibrium trade effects of existing treaties with similar set of provisions. In a second
step, the estimated increase in trade is mapped into reductions in bilateral trade costs
and imputed to EU-Mercosur country pairs to compute the general equilibrium effects of
the agreement in terms of trade creation, trade diversion, and welfare effects. Our results
indicate that the positive effects on trade and welfare stemming from the EU-Mercosur
agreement are likely to be economically important, especially for Mercosur countries,
and substantially heterogeneous both between and within the two blocs.

This paper examines the impact of an experiment in North Macedonia in which
vulnerable unemployed individuals applying to a subsidized employment program were
randomly selected to attend job interviews. Employers hiring a new employee from the
target population receive a subsidy covering the wage cost of the worker for the first six
months. Using administrative employment data, we find that attending the job interview
led to an increase of 15 percentage points in the likelihood of being employed 3.5 years
after the start of the intervention. We also find positive and statistically significant effects
on individuals’ non-cognitive and work-related skills.

Between 2009 and 2011, the Spanish banking system underwent a restructuring process
based on consolidation of savings banks. The program’s design allows us to study how
alternative forms of consolidation affect credit supply and financial stability. Compared
to bank business groups, we find that bank mergers’ market power produces a
contraction in credit supply, higher interest rates, but also a reduction in non-performing
loans. We then estimate a structural model of credit demand and supply. We show that
short-run welfare gains from improved financial stability outweigh losses from reduced
credit supply, while small long-run cost efficiencies generate large welfare increases.

Using credit-registry data for Spain and Peru, we document that four main types of
commercial credit –asset-based loans, cash flow loans, trade finance and leasing–
are easily identifiable and represent the bulk of corporate credit. We show that credit
growth dynamics and bank lending channels vary across these loan types. Moreover,
aggregate credit supply shocks previously identified in the literature appear to be driven
by individual loan types. The effects of monetary policy and the effects of the financial
crisis propagating through banks’ balance sheets are primarily driven by cash flow loans,
whereas asset-based credit is mostly insensitive to these types of effects.

This paper builds an innovative composite world trade cycle index (WTI) by means of
a dynamic factor model to perform short-term forecasts of world trade growth of both
goods and (usually neglected) services. The selection of trade indicator series is made
using a multidimensional approach, including Bayesian model averaging techniques,
dynamic correlations and Granger non-causality tests in a linear VAR framework. To
overcome the real-time forecasting challenges, the dynamic factor model is extended
to account for mixed frequencies, to deal with asynchronous data publication and to
include hard and survey data along with leading indicators. Nonlinearities are addressed
with a Markov switching model. In the empirical application, simulations analysis in
pseudo real-time suggest that: i) the global trade index is a very useful tool for tracking
and forecasting world trade in real time; ii) the model is able to infer global trade cycles
very precisely and better than several competing alternatives; and iii) global trade finance
conditions seem to lead the trade cycle, in line with the theoretical literature.

We measure the time-varying strength of macro-financial linkages within and across the
US and euro area economies by employing a large set of information for each region. In
doing so, we rely on factor models with drifting parameters where real and financial cycles
are extracted, and shocks are identified via sign and exclusion restrictions. The main
results show that the euro area is disproportionately more sensitive to shocks in the US
macroeconomy and financial sector, resulting in an asymmetric cross-border spillover
pattern between the two economies. Moreover, while macro-financial interactions have
steadily increased in the euro area since the late 1980s, they have oscillated in the US,
exhibiting very long cycles of macro-financial interdependence.

Do trade agreements with labor provisions affect trade differently from those without
such provisions? Are their effects heterogeneous with respect to the level of development
of the countries involved and the labor intensity of goods traded? In this paper we
implement a state-of-the-art structural gravity model with intra-national trade and allow
for heterogeneous effects depending on the level of enforceability of labor provisions
(weak vs. strong provisions), sector (labor vs. non-labor intensive goods), members’
development level (North vs. South), and combinations of the three dimensions. We show
that, overall, the trade effects of trade agreements with labor provisions are larger than
those without. However, we also fi nd that while exports from the South to the North
display a signifi cant increase after a signature of a trade agreements with no or weak labor
provisions, this is not the case if strong labor provisions are included in the agreement,
and that such difference tend to be larger for labor-intensive goods.

We study the macroeconomic effects of internal devaluations undertaken by a periphery
of countries belonging to a monetary union. We find that internal devaluations have
large and positive output effects in the long run. Through an expectations channel, most
of these effects carry over to the short run. Internal devaluations focused on goods
markets reforms are generally more powerful in stimulating growth than reforms aimed
at moderating wages, but the latter are less deflationary. For a monetary union with
a periphery the size of the euro area’s, the countries at the periphery benefit from
internal devaluations even at the zero lower bound (ZLB) of the nominal interest rate.
Nevertheless, when the ZLB binds, there is a case for a sequencing of reforms that
prioritizes labor policies over goods markets reforms.

We propose an empirical framework to measure the degree of weakness of the global
economy in real-time. It relies on nonlinear factor models designed to infer recessionary
episodes of heterogeneous deepness, and fitted to the largest advanced economies
(U.S., Euro Area, Japan, U.K., Canada and Australia) and emerging markets (China,
India, Russia, Brazil, Mexico and South Africa). Based on such inferences, we construct
a Global Weakness Index that has three main features. First, it can be updated as soon
as new regional data is released, as we show by measuring the economic effects of
coronavirus. Second, it provides a consistent narrative of the main regional contributors
of world economy’s weakness. Third, it allows to perform robust risk assessments based
on the probability that the level of global weakness would exceed a certain threshold of
interest in every period of time. With information up to March 2nd 2020, we show that
the Global Weakness Index already sharply increased at a speed at least comparable
to the experienced in the 2008 crisis.

We show that local central bank policies attenuate global financial cycle (GFC)’s
spillovers. For identification, we exploit GFC shocks and Brazilian interventions in FX
derivatives using three matched administrative registers: credit, foreign credit flows to
banks, and employer-employee. After U.S. Federal Reserve Taper Tantrum (followed
by strong Emerging Markets FX depreciation and volatility increase), Brazilian banks
with larger ex-ante reliance on foreign debt strongly cut credit supply, thereby reducing
firm-level employment. However, a large FX intervention program supplying derivatives
against FX risks – hedger of last resort – halves the negative effects. Finally, a 2008-2015
panel exploiting GFC shocks and local related policies confirm these results.

We postulate a nonlinear DSGE model with a financial sector and heterogeneous
households. In our model, the interaction between the supply of bonds by the financial
sector and the precautionary demand for bonds by households produces significant
endogenous aggregate risk. This risk induces an endogenous regime-switching process
for output, the risk-free rate, excess returns, debt, and leverage. The regime-switching
generates i) multimodal distributions of the variables above; ii) time-varying levels of
volatility and skewness for the same variables; and iii) supercycles of borrowing and
deleveraging. All of these are important properties of the data. In comparison, the
representative household version of the model cannot generate any of these features.
Methodologically, we discuss how nonlinear DSGE models with heterogeneous agents
can be efficiently computed using machine learning and how they can be estimated with
a likelihood function, using inference with diffusions.

A decade after the beginning of the Great Recession, flow external imbalances, measured
by the current account (CA) have narrowed markedly. However, stock or net foreign
assets (NFA) imbalances have kept increasing and have created challenges for future
macroeconomic and financial stability. To date, early warning systems (scoreboards) have
focused more on flow than on the stock variables. To approach this problem, in this paper
we analyze expansions using two complementary sets of indicators proposed by Harding
and Pagan (2002) and Gadea et al. (2017). After controlling for a large set of explanatory
variables, we find that the effect of CA imbalances is limited, except when the measures
selected take into account past CA developments or some degree of persistence. In
contrast, the evolution of NFA seems to be much more explanatory of the time it takes
to regain the level of output previous to the recession, as well as the amplitude and the
cumulation of the recoveries. Therefore, we conclude that future macro-prudential policies
should pay more attention to stock variables to measure external imbalances due to their
effects on the characteristics of recoveries.

This paper presents a text mining application, to extract information from financial
texts and use this information to create sentiment indices. In particular, the analysis
focuses on the Banco de España’s Financial Stability Reports from 2002 to 2019 in their
Spanish version and on the press reaction to these reports. To calculate the indices,
a Spanish dictionary of words with a positive, negative or neutral connotation has been
created, to the best of our knowledge the first within the context of financial stability.
The robustness of the indices is analysed by applying them to different sections of the
Report, and using different variations of the dictionary and the definition of the index.
Finally, sentiment is also measured for press reports in the days following the publication
of the Report. The results show that the list of words collected in the reference dictionary
represents a robust sample to estimate the sentiment of these texts. This tool constitutes
a valuable methodology to analyse the repercussion of financial stability reports, while
objectively quantifying the sentiment conveyed in them.

This article provides a methodology to test absolute and relative price convergence
(in mean and variance) based on a model of relative prices that includes a transition
path, and offers a way to measure the speed of price convergence across countries.
By applying this test to the European Monetary Union (EMU) price indices from 2001 to
2011, we find empirical evidence of different price level patterns and the lack of price
level convergence in the long run for most countries. In terms of the price gap between
countries, only when we compare the German with French and Italian prices, we do get
zero-gap (absolute) price level convergence. A few other countries report relative price
level convergence. These results underscore the existence of a “convergence cost” that
EMU countries with lower price levels paid and that does not tend toward zero in the
long-term in the absence of convergence. This finding might be of particular interest to
European monetary policymakers as it implies that implemented monetary policy does
not affect (benefit/harm) all EMU members equally. Monitoring the relative and absolute
price level convergence is advised to understand the monetary policy efficiency in
the long run.

This study analyses the process of economic integration in Latin America. Making use
of a structural gravity model, this paper provides an ex-post assessment of the effect of
the trade agreements (TAs) signed by Latin American countries on international trade.
We account for the last wave of TAs proliferation and estimate treaty level effects.
On average, TAs had a positive effect on Latin American trade. This holds true for both
intra-Latin American agreements and agreements between Latin American countries
and the rest of the world. However, we unveil that these average estimates cover
a substantial degree of heterogeneity across TAs. Additionally, we quantify ex-ante
general equilibrium effects on the trade volumes and welfare of Latin American
countries under different scenarios of deeper integration.

The vast macroeconomic literature trying to explain the widely observed equity home bias
disregards internationally active firms. In a DSGE model that features the endogenous choice of firms to become internationally active through either exports or foreign direct investment (FDI), we find that the optimal equity holdings of agents are biased towards domestic firms. Our finding indicates that international diversification is not as bad as empirical measures of the equity home bias suggest.

This paper brings together recent developments on the growth-at-risk methodology and the literature on the impact of macroprudential policy. For this purpose, I extend the recent proposals on the use of quantile regressions of GDP growth by including macrofinancial variables with early warning properties of systemic risk, and macroprudential measures. I identify heterogeneous effects of macroprudential policy on GDP growth, uncovering important benefits on the left tail of its distribution. The positive effect of macroprudential policy on reducing the downside risk of GDP is found to be larger than the negative impact on the median, suggesting a net positive effect in the mid-term. Nonetheless, I identify heterogeneous effects depending on the position in the financial cycle, the direction of the policy, the type of instrument, and the time elapsed since its implementation. In particular, tightening capital measures during expansions may take up to two years in evidencing benefits on growth-at-risk, while the positive impact of borrower-based measures is rapidly observed. This suggests the need of implementing capital measures, such as the countercyclical capital buffer, early enough in the cycle; while borrower-based measures can be tightened in more advanced stages. Conversely, in downturns the benefits of loosening capital measures are immediate, while those of borrower-based measures are limited. Overall, this study provides a useful framework to assess costs and benefits of macroprudential policy in terms of GDP growth, and to identify the term-structure of specific types of instruments.

In a simplied theoretical framework, we model the strategic interactions between OPEC and non-OPEC producers and the implications for the global oil market. Depending on market conditions, OPEC may find it optimal to act either as a monopolist on the residual demand curve, to move supply in-tandem with non-OPEC, or to offset changes in non-OPEC supply. We evaluate the implications of the model through a Structural Vector Auto Regression (VAR) that separates non-OPEC and OPEC production and allows OPEC to respond to supply increases in non-OPEC countries. This is done by either increasing production (Market Share Targeting) or by reducing it (Price Targeting). We find that Price Targeting shocks absorb half of the fluctuations in oil prices, which have left unexplained by a simpler model (where strategic interactions are not taken into account). Price Targeting shocks, ignored by previous studies, explain around 10 percent of oil price fluctuations and are particularly relevant in the commodity price boom of the 2000s. We confirm that the fall in oil prices at the end of 2014 was triggered by an attempt of OPEC to re-gain market shares. We also find the OPEC elasticity of supply three times as high as that of non-OPEC producers.

We explore the link between firms’ dollar bond borrowing and their FX-hedged funding
opportunities, as reflected in a positive corporate basis (the relative cost of local to synthetic currency borrowing). Consistent with previous research, we first document that firms substitute domestic for dollar borrowing when they have higher dollar revenues or long-term assets and when the corporate basis widens. Importantly, our novel firm-level dataset enables to show that when these funding opportunities appear, the currency substitution is stronger for very high-grade firms, as they can offer to investors close substitutes for safe dollar assets. However, firms with higher dollar revenues or long-term assets do not react to changes in the corporate basis. Altogether, the composition of dollar borrowers shifts when the basis widens, as high-grade firms gain importance, relative to firms with operational needs.

Demographic change and automation are two main structural trends shaping the
macroeconomy in the next decades. We present a general equilibrium model with
a tractable life-cycle structure that allows the investigation of the main transmission
mechanisms by which demography and technology affect economic growth. Due to
a trade-off between innovation and automation, lower fertility and population ageing
lead to reductions in GDP per capita growth and the labour income share. During the
demographic transition, the extent growth and factor shares are affected depends on
alternative labour market configurations and scenarios for the integration of robots
in economic activity.

The purpose of this paper is to compare the cyclical behavior of various credit impairment
accounting regimes, namely IAS 39, IFRS 9 and US GAAP. We model the impact of credit
impairments on the Prot and Loss (P&L) account under all three regimes. Our results
suggest that although IFRS 9 is less procyclical than the previous regulation (IAS 39), it is
more procyclical than US GAAP because it merely requests to provision the expected loss
of one year under Stage 1 (initial category). Instead, since US GAAP prescribes that lifetime
expected losses are fully provisioned at inception, the amount of new loans originated is
negatively correlated with realized losses. This leads to relatively higher (lower) provisions
during the upswing (downswing) phase of the financial cycle. Nevertheless, the lower
procyclicality of US GAAP seems to come at cost of a large increase in provisions.

The volume and fragmentation of regulation are important for business demography. They
may imply that the market is divided, reducing firm size and their chances of benefiting
from economies of scale. This paper has two objectives: it analyzes the results of a new
database on regulation in Spain and explores the impacts of the complexity of the regulatory
framework on business demography. The volume of new norms enacted in Spain has
increased by four-fold since the end of the 70s, reaching 11,737 regulations in 2018. The
results of our analysis indicate that the complexity of the regulatory framework, broken down
at the local level, is negatively related to the total number of firms in Spain and to firm entry
(reducing the capital of the new firms). This conclusion hides an interesting composition
effect: the complexity is negatively related to the presence of limited liability companies (SL),
which have a larger size and could take advantage of economies of scale (doing business
throughout the territory). However, it is positively related to the presence of individuals with
business activity (which are smaller) and which may have activities connected with local
regulations and local markets. The analysis proposed in this paper is relevant for the study
of productivity in Spain.

In this paper we study fiscal policy effects and fiscal space for countries in a monetary union
with different levels of public debt. We develop a dynamic stochastic general equilibrium
(DSGE) model of a two-country monetary union, calibrated to match the characteristics of Spain and Germany, in which debt sustainability is endogenously determined a la Bi (2012) to shape the responses of the risk premium on public debt. Policy shocks change the market’s expectation about future primary surplus, producing a direct effect on the sovereign risk premium and macroeconomic responses of the economy. In normal times the costs of a government spending driven fiscal consolidation in the high-debt country are greatly diminished when this consolidation improves endogenously its debt sustainability prospects. Fiscal consolidations in both members of the monetary union decrease real interest rates and amplify the reduction in risk premium in the highly-indebted country, improving union-wide output in the long run, but at the cost of lower output in the low-debt country in the short term. On the contrary, when monetary policy is constrained at the zero lower bound, the risk premium channel arising from the endogenous determination of debt sustainability becomes muted. In the ZLB, a fiscal consolidation generates deflation expectations which increase the real interest rate and may compensate partially or completely, depending on the calibration, the benefits from a lower risk premium. In this context, a fiscal expansion in the low-debt country and a consolidation in the high-debt country delivers the greater positive impact on union-wide output. Finally, the risk premium channel only affects countries with medium or low levels of public debt indirectly through the negative spillovers from other high-debt members of the monetary union.