Since the pandemic, the supply of workers with disabilities has risen substantially, a trend largely attributed to the expansion of remote work opportunities. This paper shows that increased remote work among disabled workers boosted industry productivity post-pandemic, raising real value added per hour by 2% and labor productivity by 2-6%. This paper also documents a reallocation of employment from small and young firms to larger, incumbent firms, likely reflecting the latter’s greater capacity to implement remote work at scale.

This paper introduces a novel econometric framework for identifying and modeling bank business models (BBMs). We extend the traditional cost-efficiency models by decomposing inefficiency into persistent and transient components. We propose a Bayesian nonparametric approach that adapts to the data through an infinite mixture model with predictor-dependent clustering, enabling a flexible classification of banks into distinct business models. Based on the Logit Stick-Breaking Process (LSBP), our method provides a data-driven way to capture the heterogeneity in bank strategies, allowing for dynamic transitions between business models over time.

We test the predictions of the sticky information model using a survey dataset by comparing the shoppers' accuracy in recalling the prices of regulated and comparable unregulated products. Regulated product prices change less frequently, vary less across stores and between brands, and are sold more than comparable but unregulated product prices. Therefore, shoppers would be expected to recall the regulated product prices more accurately. However, we find that shoppers are better at recalling the prices of unregulated products, in line with the sticky information model which predicts that shoppers will be more attentive to prices that change more frequently.

This paper investigates the linkage between deteriorating extreme weather conditions and anthropogenic GHG emissions and their economic impact on 40 European countries. The analysis employs the European Extreme Events Climate Index (E3CI) and its subcomponents. We find support for the contribution of human-made GHG emissions to the deterioration of underlying extreme weather conditions and their highly nonlinear pattern. We then conduct a Growth-at-Risk analysis and show that deteriorating extreme weather conditions negatively impact the entire GDP growth rate distribution. Yet the impact on the downside risk to growth is much more substantial than the upside risk.

This paper explores forward-looking ambiguity (Knightian uncertainty) in a model with homogeneous workers and credit-constrained heterogeneous entrepreneurs. Agents are ambiguity-averse, using a worst-case criterion to form expectations about future productivity. We compare our economy with one that lacks uncertainty and find that ambiguity: (i) lowers the productivity threshold for market entry, (ii) reduces the equilibrium interest rate, and (iii) shifts expenditures from entrepreneurs to workers. These results stem from persistent expectation-realization mismatches. While ambiguity does not affect stability, it alters the convergence rate to the steady state and helps explain key macroeconomic comovements.

This work examines a two-economy model where countries are identical except for their interpretation of a transitory shock in inequality, eventually affecting the aggregate Total Factor Productivity (TFP). The population consists of homogeneous workers and credit-constrained heterogeneous entrepreneurs. Along the transition path, compared with the case of perfect foresight, myopia: (i) sharply increases workers’ consumption and (ii) reduces aggregate wealth. No expectation rule, whether myopic or perfect foresight, is unambiguously dominant in terms of output, consumption, or welfare more broadly. We prove that, under myopic expectations, transitory shocks in inequality can lead to dynamic (local) instability. 

This paper explores the effect of forward-looking ambiguity (Knightian uncertainty) on labor share distribution within a macro-development model involving entrepreneurs who are heterogeneous in productivity and wealth, and homogeneous saving workers. Ambiguity-averse agents base their decisions on worst-case labor share forecasts. As workers’ expectations dominate, an endogenous hedging distribution emerges. The presence of ambiguity affects stability and induces cyclical fluctuations in labor supply, wages, and production, thereby amplifying short-term economic cycles. Capital over accumulation arises as workers save more to hedge against uncertainty. Over time, persistent ambiguity leads to capital misallocation, reducing entrepreneurial assets while boosting aggregate capital.

We study Israel’s “price rounding regulation” of January 1, 2014, which outlawed non-0 ending prices, forcing retailers to round 9 ending prices, which in many stores comprised 60%+ of all prices. We focus on the retailers' response to the price rounding regulation and find that although the government succeeded in eliminating the rounding tax, shoppers ended up paying more, not less, because of the regulation.

We present a model for data reduction and provide time-fixed indicators for macroprudential policies. Using a panel of 119 countries from 2000 to 2015, we empirically assess the effectiveness of macroprudential policies in reducing volatility in private credit. We employ an econometric model that accounts for unobserved cross-country heterogeneity and document that the impact of macroprudential policies on financial stability crucially depends on macroeconomic conditions.

The paper yields a structural account of economic integration in the Eurozone within a novel FAVAR framework. Productivity advancements have been the critical trend convergence factor, shaping long swings in real, labor market, and financial dispersion. Subdued cost-push shocks were the key driver of Eurozone nominal and competitiveness convergence throughout 2015 but have become an all-rounded divergence force since then. Fiscal discipline increased real and financial divergence during all recessionary episodes, while the ECB expansionary monetary policy was a convergence factor. Looking forward, convergence will crucially depend on how productivity dynamics and economic growth will fend off further unfavorable cost-push developments, which might become pervasive in a deglobalization-driven new macroeconomic regime.

Our study examines how national politicians react to fact-checking. A randomized field experiment reveals that fact-checking reduces factually incorrect statements for weeks. However, it does not increase correct statements; instead, politicians often replace inaccuracies with vague or unverifiable claims, indicating a shift towards more ambiguous language to avoid scrutiny.

This research examines gender disparities in entrepreneurship. It starts from the theoretical assumption that entrepreneurial decision-making follows a specific version of cumulative prospect theory. By testing a behavioral decision model through a panel data analysis using the Global Entrepreneurship Monitor’s data from 46 countries over 2013–2019, Generalized Least Squares, fixed-effects models, binomial sign tests, and signed-rank tests, it reveals that uncertainty and misperceptions differently impact men and women across business stages. The study highlights the need for gender-specific policies to support women's entrepreneurship.

The effectiveness of inflation targeting is linked to the stationarity properties of inflation. Without making apriori assumptions about the order of integration, we examine whether there is a change in the inflation persistence in one hundred and twenty-seven countries (developed and developing) using monthly data over the 1970-2021 period. For the inflation targeters, we find that the endogenously identified break dates are not consistent with the formal adoption of IT. Logit analysis reveals that inflation targeters do not experience an increased probability of a change in inflation persistence. The quality of institutions emerges as more significant for taming inflation.

This paper proposes a novel Laplace-based solution to nonlinear DSGE models that has a closed-form likelihood. We implicitly use a nonlinear approximation to the policy function that is invertible with respect to the shocks, implying that in the approximation the shocks can be recovered uniquely from some of the control variables. Using US data we estimate linear and nonlinear variants of the neoclassical growth model. We nd that a nonlinear heteroscedastic model has a much better empirical performance.

Utilizing data from the Professional Integration Survey of PhDs, and employing quantile and Recentered Influence Function regressions, the paper analyzes wage disparities across the wage distribution. Findings reveal a persistent gender wage gap across all quantiles, with research jobs offering a wage premium that does not entirely close the gap.

This paper uses time-varying Bayesian models to assess the impact of the shifting, and progressively more volatile (especially since the EU Referendum vote in 2016) macroeconomic landscape on Foreign Direct Investment (FDI) inflows to the UK. FDI inflows are depressed in response to higher UK-specific economic and geopolitical uncertainty. Rising economic policy uncertainty since the EU Referendum, has led to FDI losses of up to 0.5% of GDP.

We evaluate whether forecast disagreement emerges endogenously from belief distortions and whether it is relevant for inflation and unemployment. Local projections show that an increase in consensus pessimism leads agents to price forecast uncertainty: higher disagreement reflects lower expected profits, hence increased inflation, whereas loosening the trade-off with unemployment.

We aim to identify the determinants of non-fungible tokens (NFTs) returns. The ten most popular NFTs based on their price, trading volume, and market capitalization are examined. Twenty-three potential drivers of the returns of each NFT are considered. We employ a Bayesian LASSO model which takes into account stochastic volatility and leverage effect. The results indicate that NFTs returns are primarily driven by volatility and Ethereum returns. We find a weak connection between NFTs returns and conventional assets, such as stock, oil, and gold markets. 

We conduct two social dilemma experiments in the US and Israel with participants from both economics and non-economics majors. We use priming to manipulate the cues that the participants receive before they make their decision. We find that when participants receive cues signaling that the decision has an economic context, both economics and non-economics students tend to maximize profits. When the participants receive cues emphasizing social norms, on the other hand, both economics and non-economics students are less likely to maximize profits. We conclude that some of the differences found between the decisions of economics and non-economics students can be explained by contextual cues.

Building on Lucas (1988), we develop a model in which the impact of population dynamics on per capita GDP and human capital depends on the balance of intertemporal altruism effects towards future generations and class-size effects on an individual’s education investment. We show that there is a critical level of the class-size effect that determines whether a decline in population growth will lead to a decrease or an increase in a country’s long-run growth rate of real per capita income. We take the model to OECD data, using a semi-parametric technique. This allows us to classify countries in groups based on their long-term growth trajectories, revealing patterns not captured by previous studies on the topic. 

This paper has two contributions. Firstly we develop a novel CSV model in which the volatility follows an inverse gamma process (CSV-IG), which implies fat Student’s t tails for the observed data. We obtain an analytic expression for the likelihood of this CSV model, which facilitates the numerical calculation of the marginal and predictive likelihood for model comparison. We also show that it is possible to simulate exactly from the posterior distribution of the volatilities using mixtures of gammas. Secondly, we generalize this CSV-IG model by parsimoniously substituting conditionally homoscedastic shocks with heteroscedastic factors which interact multiplicatively with the common factor in an approximate factor model (CSV-IG-AF). An extensive empirical exercise to financial and macroeconomic data shows the new models often perform better than previously proposed approaches.

The finding of small price changes in many retail datasets is a puzzle. We show that sales volume is a possible explanation for the phenomenon, an observation overlooked in the existing literature. Small price changes are more frequent in a large retail scanner price dataset when the products’ sales volume is high. This finding is robust to more than a dozen different robustness tests.

The finding of small price changes in many retail datasets is a puzzle. We show that sales volume is a possible explanation for the phenomenon, an observation overlooked in the existing literature. Small price changes are more frequent in a large retail scanner price dataset when the products’ sales volume is high. This finding is robust to more than a dozen different robustness tests.

This paper studies the cross-market linkages between six international stock markets and the two major cryptocurrency markets during the COVID-19 pandemic and the Russian invasion of Ukraine. By employing the local (partial) Gaussian correlation approach, we find that during the COVID-19 pandemic period, both cryptocurrency markets possess limited diversification and safe haven properties, which further diminish during the war. Our findings are useful for investors in their search for understanding the differences in asymmetric connectedness between markets during extreme events.

Using data from 16 OECD countries over the period 1981-2011, this paper studies how different policy announcements affect economic growth in situations of fiscal consolidation. We find that during debt consolidation periods, announcements related to consolidation plans have no direct impact on GDP growth. Spending cut announcements have substantial negative indirect and overall effects, while tax increase announcements are negligible.

We uncover a significant amount of heterogeneity in the employment effect of deindustrialization. A large fraction of manufacturing hubs were able to adapt to the negative shock and successfully reinvent their local economy. One important factor that raised the probability of recovery was the initial level of residents' human capital.

We show that the S&P 500's instantaneous response to surprises in U.S. macroeconomic announcements depends on the level of long-term stock market volatility. When long-term volatility is high, stock returns are more sensitive to news, and there is a pronounced asymmetry in the response to good and bad news. We explain this by combining the Campbell-Shiller log-linear present value framework with a two-component volatility model for the conditional variance of cash flow news and allowing for volatility feedback.

This paper addresses the unexplained phenomenon of gender differences in entrepreneurial decision-making, particularly in business sectors involving innovation and risk. It provides a theoretical framework involving models on risk, ambiguity, perceptions of risk as in cumulative prospect theory, and asymmetric information. By detailing and analyzing theoretical gender-type differences and their effects on entrepreneurial decision-making under uncertainties, this paper finds that traditional one-dimensional gender policies are not sufficient to address complex gender issues. Rather, it suggests a multi-dimensional policy approach that combines traditional gender policies and policies for long-term sustainability.

In this paper, we assess climate risks for the European stock market within the context of Alessi et al. (2023) greenness and transparency factor. We show that measures of returns spreads of green vs. brown investment might reflect climate risks and assets' exposition to systematic macro-financial risk factors. These latter factors should be filtered out to measure climate risks accurately. We show that climate risks are priced in the European stock market by focusing on aggregate, industry, and company-level data. We propose a market-based green rating procedure and illustrate its implementation using a sample of over 800 non-transparent firms.

We revisit the tourism-led growth hypothesis by utilizing a panel set of 108 countries over the period 1996-2017. We quantify the effects of tourism on the entire conditional distribution of economic growth for both relatively poor and relatively rich countries within a panel quantile regression framework. We find that the lower the conditional growth rate a country experiences the more important is tourism development for the conditional growth distribution. Moreover, tourism specialization is beneficial only at higher quantiles of conditional growth distribution and only for developed countries.

The persistent trade and economic imbalances between the south and north euro area countries generated severe strains for the euro following the global financial crisis. We assess alternative scenarios to restore the trade imbalances within the euro area. We use a Bayesian VECM SVAR with stochastic volatility in a Global-VAR, in which theory-consistent, long- and short-run restrictions are imposed.

The persistent trade and economic imbalances between the south and north euro area countries generated severe strains for the euro following the global financial crisis. We assess alternative scenarios to restore the trade imbalances within the euro area. We use a Bayesian VECM SVAR with stochastic volatility in a Global-VAR, in which theory-consistent, long- and short-run restrictions are imposed.

We obtain a novel analytic expression of the likelihood for a stationary inverse gamma Stochastic Volatility (SV) model. This allows us to obtain the Maximum Likelihood Estimator. Further, we obtain analytically both the filtering and smoothing distributions for the inverse volatilities as a mixture of gammas. This allows exact sampling. 

We study the price rigidity of regular and sale prices, using regular and transaction price data from three large Canadian stores with different pricing formats (Every-Day-Low-Price, Hi-Lo, and Hybrid). We add filtered price and reference price series and study the rigidity of the four-price series. Regular price rigidity varies with store formats because different format stores treat sale prices differently, and consequently define regular prices differently. 

We examine the asymmetric and nonlinear nature of the cross- and intra-market linkages of eleven EMU sovereign bond and CDS markets during 2006-2018. We find that contagion phenomena occurred during two phases, i.e. late 2009 through mid-2011 and, again in late 2011. Consistent with their “too big to bail out” status, Italy and Spain emerged as pivotal for the evolution of sovereign credit risk across the Eurozone. Our examination highlights the importance of credit risk over liquidity risk and the containment effect of the naked CDS ban. 

We test whether firm-specific demand shocks impact wages and disentangle predictions from wage bargaining (surplus variation) and wage posting (size variation). We leverage the random ending of procurement auctions in Brazil to get the random assignment of the winner and runner-up. Winning a contract increases wages. We find evidence of bargaining.  

This paper uses a quantile panel framework to examine the sectoral shifts hypothesis for the US regional labor marketing in the 48 US states. It investigates the asymmetric relationship between sectoral labor reallocation and unemployment fluctuations. The empirical evidence suggests that the impact of the employment dispersion index is relatively small and insignificant for lower levels of unemployment but becomes positive and highly significant for higher rates. Our findings show the asymmetry of reallocation disturbances in the US labor market.  

We propose a multicountry quantile factor augmented vector autoregression (QFAVAR) to model heterogeneities both across countries and across characteristics of the distributions of macroeconomic time series. The presence of quantile factors allows for summarizing these two heterogeneities in a parsimonious way. We develop two algorithms for posterior inference that feature varying levels of trade-off between estimation precision and computational speed. Using monthly data for the euro area, we establish the good empirical properties of the QFAVAR as a tool for assessing the effects of global shocks on country-level macroeconomic risks. 

In addition to realized earnings and employment shocks, forward-looking individuals are presumed to condition their consumption and labor supply decisions on their subjective beliefs about future labor market risks. This paper analyzes these perceptions of earnings and employment risks using rich monthly panel data. It documents considerable individual heterogeneity in expected earnings growth and earnings growth uncertainty and in the perceived likelihood of a voluntary and involuntary job exit. It provides novel evidence on the perceived persistence in earnings growth shocks and on the association between future earnings and spending growth. 

We empirically identify the state of the US housing market and set state-dependent policy rules to smooth the housing cycle. We estimate a three-state Markov-switching model of housing prices in which mortgage debt is the state-dependent variable, and propose a state-contingent policy rule fed with the probabilities of being in each state. We apply such a rule to set a housing countercyclical capital buffer (SCCyB) and a time-varying home mortgage interest deduction rule, showing its relevance for macroprudential policy. 

In light of the high levels of systemic risks and the elevated probability of a crisis occurring, understanding the effectiveness of macro-prudential policies is becoming increasingly crucial. We incorporate a collateral-based macro-prudential policy into a two-agent New Keynesian model, this policy adjusts counter-cyclically to the state of the borrowing sector. We show that regulators accommodate high delinquency rates by allowing for tighter collateral requirements. An active macro-prudential policy amplifies the impact of a monetary policy shock on output and labor supply, and this policy emerges as a potential tool to prevent the risk of delinquency in the short run. 

We combine choice data with observations obtained while agents form their choices to examine aspects of the interactive decision-making process. We develop a methodological approach to characterize the distributions of choice and process data with minimal restrictions on their joint behavior and on the motives, and calculations, of agents. 

When agents' information is imperfect and dispersed, existing measures of macroeconomic uncertainty based on the forecast error variance have two distinct drivers: the variance of the economic shock and the variance of the information dispersion. We use these implications to identify empirically the effects of agreed and disagreed uncertainty shocks, based on a novel measure of consumer disagreement derived from survey expectations. Disagreed uncertainty has no discernible economic effects and is benign for economic activity, but agreed uncertainty exerts significant depressing effects on a broad spectrum of macroeconomic indicators. 

This study employs a Bayesian Structural Vector Autoregression (SVAR) to compare the implications of traditional identification approaches (SVAR with zero/sign restrictions) with those from the baseline model (Bayesian SVAR) for the case of the US. We find that the baseline model implies more plausible posterior price elasticities of oil supply and demand and a more profound effect of oil supply shocks on oil prices. Nonetheless, all models provide qualitatively similar conclusions for the effects of oil market shocks on the US stock market. 

This paper introduces a new core inflation measure, the structural core inflation rate, which bears the interpretation of expected headline inflation, conditional to medium to long-term demand and supply-side developments. It shows smoothness and trending properties, economic content, and forecasting ability for headline inflation and other available core inflation measures. Concerning recent developments, since mid-2021, core inflation has been on a downward trend, landing at about 3% in 2022. Idiosyncratic supply chains, energy markets, and geopolitical tensions are currently the major threats to price stability. A stagflation scenario cum weakening overall financial conditions might be lurking ahead. 

In this paper, we examine the existence of sentiment exposure in oil price returns. We augment the SVAR model of Kilian and Park (International Economic Review, 2009, 50, 1267–1287) by including the effects of (1) investors' sentiment proxied by Google’s search volume index, (2) economic policy uncertainty (EPU) and (3) time variation in both coefficients and the variance-covariance matrix. Our empirical results show that changes in investor attention do exhibit a significant long-lasting impact on oil and stock market returns. 

We assess the role of cognitive convenience in the popularity and rigidity of 0ending prices in convenience settings. Studies show that 0-ending prices are common at convenience stores because of the transaction convenience that 0-ending prices offer. Using large store-level retail CPI data, we find that 0-ending prices are popular and rigid at convenience stores even when they offer little transaction convenience. 

We study the determinants of inventory accumulation in a structural VAR framework with news shocks. Specifically, we investigate how news shocks affect two key determinants of inventory movements, namely rates of return and marginal costs. We establish that inventories react strongly and positively to news about future increases in total factor productivity. We provide evidence that changes in external and internal rates of return are central to the transmission of such news shocks. We do not find evidence for a dominant role of marginal costs.

Governments have implemented school closures and online learning as one of the main tools to reduce the spread of Covid-19. Despite the potential benefits in terms of the reduction of cases, the educational costs of these policies may be dramatic. This work identifies the educational costs, expressed as a decrease in test scores, for the whole universe of Italian students attending the 5th, 8th and 13th grades of the school cycle during the 2021/22 school year.  The results suggest a national average loss between 1.6-4.1% and 0.5-2.4% in Mathematics and Italian test scores, respectively. 

Recent studies in psychology and neuroscience offer systematic evidence that fictional works exert a surprisingly strong influence on readers and have the power to shape their opinions and worldviews. Building on these findings, we study ‘Potterian economics’, the economic ideas, insights, and structure, found in Harry Potter books, to assess how the books might affect economic literacy. We find that some of the principles of Potterian economics are consistent with economists’ models. Many other principles, however, are distorted and contain numerous inaccuracies, contradicting professional economists’ views and insights. 

This paper proposes strategies to detect time reversibility in stationary stochastic processes by using the properties of mixed causal and noncausal models. It shows that they can also be used for non-stationary processes when the trend component is computed with the Hodrick-Prescott filter rendering a time-reversible closed-form solution. This paper also links the concept of an environmental tipping point to the statistical property of time irreversibility and assesses fourteen climate indicators. We find evidence of time irreversibility in GHG emissions, global temperature, global sea levels, sea ice area, and some natural oscillation indices. While not conclusive, our findings urge the implementation of correction policies.

We condition on the state of the pandemic to assess the impact of nonpharmaceutical interventions and economic stimulus policies on the excess unemployment insurance claims in the United States. We focus on weekly data between February 2020 and January 2021 and motivate our analysis by the theoretical framework of the second-wave SIR-macro type models to build a panel Vector AutoRegressive (VAR) specification. Non-pharmaceutical interventions become effective immediately and impact the labor market negatively. Economic stimulus takes about a month to turn effective and only partially eases the economic welfare losses. 

We study the effects of taxation on the growth rate of the real per capita GDP in a sample of 21 OECD countries, over the period 1965-2010. We employ a Finite Mixture Model which combines features from mixed effect models for panel data and cluster analysis methods to account for country-specific unobserved heterogeneity. Our results suggest that taxes have a negative impact on growth: a 10% cut in the personal income tax rate (respectively corporate income tax rate) may raise the GDP growth rate by 0.6% (respectively 0.3 %).

We show analytically that linear interpolation reduces shock-persistence of a nonstationary process, but the interpolated series can still exhibit greater shock-persistence than a pure random walk. Moreover, linear interpolation makes the series periodically nonstationary, with parameters of the DGP and the length of the interpolation time-segments affecting shock-persistence in conflicting ways.

We study the scholars’ reaction to the 2008 financial crisis by applying LDA and dynamic topic modeling algorithms to the texts of 14,270 NBER working papers published in 1999–2016. Scholars were “slow-to-see” the crisis coming, but they were “fast-to-act” as the crisis unraveled. Their initial response to the ongoing Covid-19 crisis is consistent with these conclusions.

Is actual inequality accurately translated into people’s perceptions, and what are the genuine hopes of citizens? Our contribution offers insights into how the reality and two subjective dimensions of inequality, namely perceptions, and desires, interact. Using data from the Eurobarometer, we study the main patterns of different “types” of inequality in the European NUTS2 regions. Considering the role of attitudes and beliefs, the residents of the same region are typically found to hold a similar perception of how unequal their society is. Moreover, and somewhat surprisingly, the reality is contrary to people’s perception since low (high) actual inequality in the region is often reflected in its overestimated (underestimated) perception. Our findings may assist policy-makers and other interested stakeholders in designing dedicated policies to counteract inequality in all its forms.

This paper reviews the recent development in the field of Bayesian model determination with emphasis on high dimensional inference. We begin with a linear regression setting in order to introduce various classes of priors that lead to shrinkage/sparse estimators of comparable value to popular penalized likelihood estimators (e.g. ridge, lasso). We explore various methods of exact and approximate inference and discuss their pros and cons. Finally, we explore how priors developed for the simple regression setting can be extended in a straightforward way to various classes of interesting econometric models. In particular, the following case studies are considered, that demonstrate the application of Bayesian shrinkage and variable selection strategies to popular econometric contexts: i) vector autoregressive models; ii) factor models; iii) time-varying parameter regressions; iv) confounder selection in treatment effect models; and v) quantile regression models. 

We study an economy characterized by competitive search and asymmetric information. In the baseline model with indivisible goods, we show that, when the number of potential buyers is fixed, inflation decreases markups. This, in turn, increases aggregate output and ex-ante welfare. When goods are divisible the negative effect of inflation on markups holds for unconstrained agents but is ambiguous for constrained agents. Still, optimal monetary policy implies a positive nominal rate. When there is buyers’ free entry, asymmetric information causes a congestion effect that can be corrected by monetary policy. 

We identify total factor productivity (TFP) news shocks using standard VAR methodology and document a new stylized fact: in response to news about future increases in TFP, inventories rise and comove positively with other major macroeconomic aggregates. We derive the conditions required to generate a procyclical inventory response by using a wedges approach. We show that the presence of knowledge capital accumulated through learning-by-doing moves the wedges to qualitatively match the empirical behavior. Our findings support the view that news shocks are an important driver of aggregate fluctuations.

A large literature suggests that the expected equity risk premium is countercyclical. Using a variety of different measures for this risk premium, we document that it also exhibits growth asymmetry, i.e. the risk premium rises sharply in recessions and declines much more gradually during the following recoveries. We show that a model with recursive preferences, in which agents cannot perfectly observe the state of current productivity, can generate the observed asymmetry in the risk premium.  The model is also successful in generating the growth asymmetry in macroeconomic aggregates observed in the data.

Financial development and financial reforms affect economic growth, but less is known on how this effect varies across different levels of the conditional distribution of the growth rates. We examine this by using panel data for 81 countries for more than 30 years. The findings indicate that financial reforms are important determinants of growth, especially when a country faces relatively low levels of economic growth. We reveal that the components of financial reforms, which are more important for economic growth, are the supervision of banks and the regulation of securities markets.

We use data from three large stores with different pricing formats (EDLP/Hi-Lo/Hybrid) located within a 1-km radius. The data contain both the actual transaction and the actual regular prices, which we combine with two “generated” regular price series and study their rigidity. Regular-price rigidity varies with store-formats because different format stores define regular-prices differently. We interpret the findings in the context of the store pricing format distribution across the US. 

This policy brief warns about the risks of discontinuing the policy responses to the COVID19 crisis by pursuing exit strategies too early and/or too sharply. It outlines a comprehensive strategy for limiting such risks globally and offers an in-depth discussion of the European situation. 

We propose the information matrix test to assess the constancy of mean and variance parameters in vector autoregressions. We additively decompose it into several orthogonal components: conditional heteroskedasticity and asymmetry of the innovations, and their unconditional skewness and kurtosis. Our procedures detect variation in the autoregressive coefficients and residual covariance matrix of a VAR for the US GDP growth rate and the statistical discrepancy, but they fail to detect any covariation between those two sets of coefficients. 

This paper studies models for forecasting day-ahead hourly electricity prices.  Forecasts of demand, in-feed from renewable energy sources (RES), fossil fuel prices, and physical flows are all included in linear and nonlinear specifications, ranging in the class of ARFIMA-GARCH models hence including parsimonious autoregressive specifications known as expert-type models. An extended expert model is found to produce accurate point and density forecasts. Using professional and more timely predictions of consumption and RES improves the forecast accuracy of electricity prices more than predictions freely available to researchers 

We extend the existing understanding of the relation between oil prices and stock markets in two ways: (1) by evaluating the effects of the oil market on the U.S. stock market, at an aggregate level and for all forty-nine U.S. industry-specific portfolios, and (2) by scrutinizing the dynamic nature of this relation, by fitting a Structural Vector Autoregression (SVAR) specification for a large set of rolling samples with a fixed size. Results indicate that the effect of oil prices on the U.S. stock market depends on the type and timing of the shock.

This paper investigates the extent of convergence club formation in retail gasoline prices in Canada. The findings suggest that the retail gasoline markets are not integrated in terms of requiring multiple numbers of convergence clubs to explain relative price movements across cities. In addition to this, wholesale gasoline prices cities are probably less integrated than retail prices. Key drivers of retail price divergence across cities include distances between cities and the need to be explicit on distinguishing fuel quality.

We empirically investigate the effectiveness of environmental and energy policies, complying with legal requirements or followed voluntarily by firms, on the pro-environmental efforts of 63 listed firms in Italy in the years 2008-2019. Our results show that the social costs of climate change are not internalized by listed companies and that macroeconomic interventions are effective to fight climate change where voluntary actions fail.

This survey provides (i) a historical overview of climate change awareness worldwide, (ii) a guide to the most widely used datasets; (iii) a detailed review of the main socio-economic and climatological determinants of climate change awareness; and (iv) a summary of the main implications of these findings in terms of public policy responses.

We propose a new set of indices to capture the multidimensionality of a country’s institutional quality. Our indices are obtained by employing a dimension reduction approach on the institutional variables provided by the Frazer Institute (2018). We estimate the impact that our measures of institutional quality have on the level and the growth rate of per capita GDP, using a large sample of countries over the period 1980-2015. The empirical evidence points to a significant impact of institutions, especially for low- and middle-income countries.

We examine a theoretical model of liquidity with three assets - money, government bonds, and equity- that are used for transaction purposes. Money and bonds complement each other in the payment system. The liquidity of equity is derived as an equilibrium outcome. Liquidity cycles arise from the loss of conÖdence of the traders in the liquidity of the system. Both open market operations and credit easing play a beneficial role for different purposes. 

We undertake Monte Carlo simulation experiments to examine the effect of changing the frequency of observations and the data span on the Phillips, Shi, and Yu (2015) Generalised Supremum ADF (GSADF) test for explosive behavior via Monte Carlo simulations. We find that when a series is characterized by multiple bubbles (periodically collapsing), decreasing the frequency of observations is associated with profound power losses for the test. The empirical relevance of the findings is shown in relation to the US housing market.

In this note, we show that the information matrix test for a multivariate normal random vector coincides with the sum of the two-moment tests that look at the means of all the different third- and fourth-order multivariate Hermite polynomials, respectively. We also exploit the numerical invariance of the test statistic to affine transformations of the observed variables to simulate its exact, parameter-free, finite sample distribution to any desired degree of accuracy for any dimension of the random vector and sample size. 

This paper develops a dynamic investment model for satellites and studies the economic consequences of orbital debris for commercial outer-space activities. We find that the optimal quantity of satellites is a negative function of the amount of debris. The paper derives a simple expression for the maximum number of satellites to prevent the Kessler syndrome. The model is simulated to study the effects of a decline in the launch cost and the increasing number of satellites per launch. 

We document round price rigidity in runaway inflation: more round prices are less likely to adjust. When they adjust, the average adjustment is large. Thus, price adjustment barriers round prices face, are strong enough to delay price adjustments even in a period when 85% of the prices change every month.

This paper investigates the determinants of the CDS index considering a large set of explanatory variables within a Markov switching model in a sample post-subprime financial crisis up to the COVID-19 pandemic. Results indicate that more than two regimes are significant to model CDS spreads, and the four-regime model is the preferred one. The fourth regime activated during the COVID-19 pandemic and also in high volatility periods  

This paper describes the results from a questionnaire administered to students of schools in the Emilia Romagna Region. The results show a significant increase in students’ knowledge following a 10-hour course attended by school teachers and held by personnel of the Bank of Italy. 

In this paper, we introduce a new time-domain decomposition to disentangle the financial cycle and the concurrent long swings in economic activity. Based on this approach, we introduce a set of new composite indexes of macro-financial conditions for the euro area and assess their information content. In particular, with reference to the current pandemics, the indicators suggest that most of the GDP contraction has been of short-term, cyclical nature. Yet our evidence suggests that the financial cycle might have currently achieved a peak area. Hence, the risk of further, deeper disruptions is high, particularly in so far as a new sovereign/corporate debt crisis were not eventually avoided 

This paper analyzes the macroeconomic and distributional effects of declining labor share as observed during the last decades. We use a neoclassical general equilibrium model with two types of households, workers and capitalists, endowed with a CES production function, in which the distributional parameter matches labor share. We show that both capitalists’ and workers’ income increase as labor income declines depending on the elasticity of substitution between capital and labor. The effect of labor share changes on income distribution does not depend on the elasticity of substitution, and hence, relative income and relative consumption decrease for workers, increasing inequality. 

We suggest a multiplicative factor multi-frequency component GARCH model which exploits the empirical fact that the daily standardized forecast errors of standard GARCH models behave counter-cyclical when averaged at a lower frequency. For the new model, we derive the unconditional variance of the returns, the news impact function, and multi-step-ahead volatility forecasts. We apply the model to the S&P 500, the FTSE 100, and the Hang Seng Index. We show that the long-term component of stock market volatility is driven by news about the macroeconomic outlook and monetary policy as well as policy-related news. The new component model significantly outperforms the nested one-component (GJR) GARCH and several HAR-type models in terms of out-of-sample forecasting . 

Based on a new survey of German households, we investigate the role that information channels and lifetime experience play in households’ inflation expectations. We show that information channels households use to inform themselves about monetary policy are closely related to their socioeconomic characteristics. These have a major influence on the level of perceived past and expected future inflation. The expected future change in inflation, however, is strongly influenced by individuals' experience of this variable. Overall, households appear to obtain inflation numbers from the media, but their ‘economic model’ is shaped by experience.  

This study examines the co-determination of cross-sectional inequality of income and consumption in a setting that allows for intra-family persistence. Estimation of the model delivers measures of inter-generational persistence in conjunction with the variance-covariance structure of all innovations to the income and consumption processes. This structure can be used to construct counterfactual scenarios that restrict different parental influences. We use the model to extrapolate the influence of family background over multiple generations and examine alternative hypothetical steady states for cross-sectional inequality. 

We propose improved output (GDP) measures under the assumption that alternative measurements in levels do not systematically diverge from each other over the long run. While economic activity, like many other macroaggregates, arguably displays a strong stochastic trend, one would expect statistical discrepancies to mean-revert. In that case, measurements in levels would share a common trend. Somewhat surprisingly, though, the standard practice is to rely on models that do not impose this common trend. In this respect, one of our main goals is to explore the implications of not doing so for both parameter estimators and smoothed estimates of latent variables.

We develop a game-theoretic model and conduct a survey on Ontarians to understand opposition to mandatory masks during the pandemic. Those who are young, healthy, Canadian-born, less educated, or politically conservative males are more likely to oppose mandatory masks, as are individuals who do not believe in climate change, doctors, or elected officials. 

A Bayesian dynamic compositional model is introduced that can deal with combining a large set of predictive densities. It extends the mixture of experts and the smoothly mixing regression models by allowing for combination weight dependence across models and time. A compositional model with Logistic-normal noise is specified for the latent weight dynamics and the class-preserving property of the logistic-normal is used to reduce the dimension of the latent space and to build a compositional factor model. The projection used in the dimensionality reduction is based on a dynamic clustering process which partitions the large set of predictive densities into a smaller number of subsets. We exploit the state space form of the model to provide an efficient inference procedure based on Particle MCMC. Financial applications are also discussed.

We offer two types of evidence on the cost of breaching an implicit contract between the Coca-Cola Company and its consumers, which included a promise of constant quality. First, we document a case in 1930 when the Company chose to avoid quality adjustment by incurring a permanently higher marginal cost of production, instead of a one-time increase in the fixed cost. Second, we study the company’s 1985 introduction of “New Coke” to replace the original beverage. Using the model of exit, voice, and loyalty, we argue that the public outcry that followed New Coke’s introduction was a response to the implicit contract breach .

We empirically investigate the existence of the Environmental Kuznets Curve (EKC) focusing on a sample of 39 countries in the period 1996-2014. Our results show that the inverted U-shaped relationship between environmental stress and economic development holds independently of the quality of political institutions and environment related taxes. Yet an increase in the environmental tax revenue has the expected reducing effect on environmental degradation only in countries with more consolidated democratic institutions, higher civil society participation and less corrupt governments.

Our survey elicits Ontarians’ compliance with current social-distancing regulations and proposed regulations that impose non-compliance fines or grant wage subsidies to stay home. Risk-of-infection variables (health, age, work outside home, regional COVID-19 cases), gender, political beliefs, risk and time preferences all predict compliance. Fines and subsidies effectively promote compliance .

We put forward the time varying parameter SIRD model to track the real-time stance of the Covid-19 pandemic. The model permits a flexible yet computational inexpensive framework using the `autoregressive score modelling’ structure. Results show that countries including US, Brazil and Russia are not able to contain the pandemic yet while Iran and Korea are likely to experience the second wave as of mid June.

We examine the impact of oil supply and demand shocks on gasoline prices and consumer sentiment in the Euro Area. We find that aggregate consumer sentiment deteriorates notably as a response to positive shocks to gasoline prices but is not affected by positive oil-specific demand shocks. In other words, consumer sentiment is affected primarily by unexpected changes in gasoline prices at the pump rather than unexpected changes in crude oil prices. 

We investigate recycling, using Italian survey data. People with an interest in environmental issues or belonging to an environmental association recycle more, while people living in an environment they perceive as deteriorated recycle less. We interpret these findings using insights from psychology and behavioral economics.  

We study the optimal tax burden on labor and capital in a scale-less prototypical Schumpeterian model with elastic labor. As R&D productivity is decreasing in the size of the economy labor and growth are not positively related however the optimal tax on capital is sizable for standard parameters' values  

This paper investigates the relationship between oil prices and stock markets of selected oil importers and oil exporters at the time of the COVID-19 pandemic. It provides robust evidence in favour of energy contagion, in terms of significantly higher correlations between oil and stock markets returns during turbulent phases in the oil market.  

We design a series of laboratory experiments designed to investigate the effects of purchasing insurance and pre-filled claim forms on exaggerated loss reporting. Consistent with an ‘entitlement bias’, we find dishonest reporting is more prevalent among the insured than the uninsured. Pre-filled claim amounts only modestly constrain dishonest reporting   

A field experiment at seemingly highly competitive Israeli produce markets reveals that female buyers are offered larger and more frequent price discounts than males, especially attractive females. No other buyer characteristic predicts the likelihood or size of a discount. Search costs and vendor price-setting discretion help understand our findings.  

This paper shows that there is a simple way to generate statistically significant and economically valuable equity premium predictions in both expansions and recessions: use a forecast combination of one predictor that generates cyclical forecasts and one predictor that generates countercyclical forecasts. A prominent two-predictor forecast combination that performs well is the dividend yield, which delivers better predictions in expansions, and the short rate, which delivers better predictions in recessions.  

This paper shows that public attitudes on climate change in Europe over the last decade have evolved according to the “S-shaped” information dissemination model, conditional to various socioeconomic and climatological factors. 

In this paper spillovers from FDI are identified by comparing TFP among domestic plants in districts where a foreign plant produces and where FDI was licensed but not yet operational. Over the four years starting with the year of the opening, the TFP of domestic plants is 11 percent higher in treated districts

This paper shows  that the early stages of the Covid-19 pandemic had a disproportionately negative impact on employment and hours in lower-paying occupations. Workers who were employed in lower-paying occupations in mid-February 2020 experienced larger employment and hours reductions by mid-March 2020 compared to workers who were employed in higher-paying occupations. 

This paper  explores the impact of economic uncertainty related to global pandemics on the volatility of the S&P GSCI commodity index as well as on the sub-indexes of crude oil and gold. The results show that uncertainty related to pandemics have a strong negative impact on the volatility of commodity markets and especially on crude oil market, while the effect on gold market is positive but less significant.

We examine the long run relationship between European far right, radical left and unemployment. A unique dataset is compiled for 31 European countries that span from 1900 to 2013. It is shown that an increase in unemployment and radical left increase the far-right vote share. 

This paper uses a Global VAR model for 28 developed and developing countries to examine the interaction between the global trade imbalances and their impact within the euro area framework. It is found that an expansionary policy of the North euro area and increased competitiveness in the South euro area could alleviate trade imbalances of the debtor euro area economies.

This paper shows proposes a new Bayesian sampling scheme for VAR inference using sign restrictions. We build on a factor model decomposition of the reduced-form VAR disturbances, which are assumed to be driven by a few fundamental factors/shocks. The outcome is a computationally efficient algorithm that allows to jointly sample VAR parameters as well as decompositions of the covariance matrix satisfying desired sign restrictions.

This paper develops a new decomposition of price variance based on the observation that store expensiveness is not universal but varies across consumers depending on the basket they consume. It is found that the ability to choose the cheapest store for one's basket is the main source of variance in consumer savings.

While pay-as-you-go pension systems are political stable due to ratchet effect, funded pension systems are  not, as they cannot rely on the same mechanism. By means of a calibrated overlapping generations model, this paper then shows that asset capture which occurred amidst the global financial crisis of 2008 would have likely happened anyway, because asset capture always has political majority. While introducing funding implies delayed gains and immediate costs, the asset capture allows for immediate gains and delayed costs.

The typical model with fully rational agents predicts that about 60% of old-age consumption is financed through private voluntary savings. This is clearly at odds with the observational data. This paper shows that fiscal incentives to saving for old-age are not very effective in raising savings even among the incompletely rational agents. The incentives direct most of the transfers to those agents who need it the least. The key to raising old-age savings is providing agents with a saving vehicle that yields a market return on capital. 

This paper shows that economists were not engaged sufficiently in crises studies before the 2008 crisis. However, they responded dramatically to the crisis by switching their focus and efforts to studying and understanding the crisis, its causes and its consequences.

This paper points out that Canada spends more than Italy on health in per capita terms and as a share of GDP and yet Italy’s two main health indicators as measured by life expectancy and infant mortality are better and have improved more than Canada’s in recent years. It is argued that a key difference between Canada and Italy is that Italy spends relatively more on social transfers – particularly pensions. 

This paper proposes a covariance matrix estimator based on the l1-regularized approximate factor model. The sparse approximate factor (SAF) estimator allows for weak factors and hence relaxes the pervasiveness assumption generally adopted for the standard factor model. In a portfolio forecasting application, the estimator outperforms alternative portfolio strategies including the 1/N-strategy.

This paper examines the link between worker-job mismatch and productivity. It is found that  productivity is dampened most when university educated workers are employed in occupations generally requiring community-college or high school education, thus leaving human capital idle.

This paper shows that increasing inequality and  production concentration in superstar firms are linked. Data from 14 European countries shows robust evidence of a positive and significant correlation between concentration and firm-level wage dispersion.