Search

This paper examines the interconnection between four implied volatility indices representative of the investors' consensus view of expected stock market volatility at different maturities during the period from 3 January 2011 to 4 May 2018. To this end, we first perform static analysis to measure the total volatility connectedness in the entire period using a framework proposed by Diebold and Yilmaz (J Econ 182: 119–134, 2014). Second, we apply a dynamic analysis to evaluate both the net directional connectedness for each market using the TVP-VAR connectedness approach developed by Antonakakis and Gabauer (Refined measures of dynamic connectedness based on TVP-VAR. MPRA, Working Paper No. 78282, 2017). Our results suggest that 72.27% of the total variance of the forecast errors is explained by shocks across the examined maturities, indicating that the remainder 27.73% of the variation is due to idiosyncratic shocks. Furthermore, we find that volatility connectedness varies over time, with a surge during periods of increasing economic and financial instability. Our results are robust to control by macroeconomic and uncertainty factors, and persistent across US and European implied volatility indices. [ABSTRACT FROM AUTHOR]

This paper examines whether the SAH orders, implemented in the USA from mid-March to late May 2020, improved air quality in the northeastern states. The estimates are based on panel data from the Environmental Protection Agency and an identification strategy that exploits the exogenous variation in the timing of the SAH orders. We find that the SAH orders reduced the concentrations of the air pollutants nitrogen dioxide ( NO 2 ) and carbon monoxide (CO), whose dominant source is motor vehicle emissions, by approximately 24% and 13%, respectively. The effects were larger for areas of high population density and areas near major roads. We also find that the reductions got smaller, and air pollution gradually approached normal levels, after the orders were lifted. This suggests that the air quality improvements were temporary. [ABSTRACT FROM AUTHOR]

This paper aims to investigate whether the predictive performance and behaviour of professional forecasters are different during the COVID-19 pandemic as compared with the global financial crisis of 2008 and normal times. To this end, we use a survey of professional forecasters in Singapore collated by the central bank to analyse the forecasting records for GDP growth and CPI inflation for the period 2000Q1–2021Q4. We first examine the point forecasts to document the extent of forecast failure during the two crises and explore various explanations for it, such as leader-following and herding behaviour. Then, using percentile-based summary measures of probability distribution forecasts, we study how the degree of consensus and extent of subjective uncertainty among forecasters were affected by crisis conditions. A trend break is observed in the subjective uncertainty associated with growth projections after the onset of the COVID-19 crisis. In contrast, both subjective uncertainty and the degree of consensus in inflation projections were essentially unchanged in crises, suggesting that the short-term inflation expectations of forecasters were strongly anchored. [ABSTRACT FROM AUTHOR]

Redistribution is one of the most central functions of modern government. Against the backdrop of rising income inequality in many countries, policymakers and economists call for redistributive policies to address the rising inequality directly. Yet, there has been little systematic analysis of whether and how inequality influences redistribution and of the role of economic, political and institutional factors of redistribution. Our paper fills this important gap in the literature. To our knowledge, this is the first paper that systematically analyzes and presents evidence from a large panel of countries over 1967–2014 that high-income inequality is consistently associated with greater redistribution. Making it richer, evidence shows the role of economic factors such as trade openness, old age dependency, and financial development, and suggests that political institutions are important factors in understanding a cross-country variation in the size of redistribution. Extensive robustness checks confirm the results. [ABSTRACT FROM AUTHOR]

Hodrick–Prescott (HP) filter is a popular trend filtering method for univariate macroeconomic time series such as real gross domestic product. This paper considers the quantile regression version of HP filter (qHP filter), which is a filtering method defined by replacing quadratic loss function of HP filter with quantile regression loss function. One of the essential properties of quantile regression is that if the regression includes intercept, then the ratio of negative residuals can be almost controlled. Does the suggested qHP filter also have the property? This paper answers this question. In addition to the main result, we provide an empirical illustration. [ABSTRACT FROM AUTHOR]

In this paper, we analyze the forecasting performance associated with using machine learning, shrinkage, and variable selection methods during a historical period that contains the Great Recession of 2008. We find that these methods are most useful during "low" GDP growth periods, while simple autoregressive models are adequate during "high growth" periods. This finding stems from the introduction of very simple "hybrid" models that employ dynamic recursive (rolling) thresholding in order to switch between benchmark linear models and more complex index-driven models, depending on GDP growth conditions. In the context of predicting both quarterly real GDP growth and CPI inflation, these hybrid models are found to be superior, for all forecast horizons. When comparing the hybrid models against a host of alternatives, mean square forecast error gains reach as high as 35%, during the Great Recession, and remain significant throughout our entire prediction period. Additionally, the very best short-term GDP forecasting models contain variants of the Aruoba et al. (2009) business conditions index, although these models are most useful when diffusion indices are also incorporated. Thus, mixing mixed frequency and diffusion indices matters. Finally, across all experiments, we find strong new evidence of the usefulness of survey predictions, including those from the Survey of Professional Forecasters, and those from the Livingston Survey. While we leave the examination of alternative datasets, such as those including other recessionary periods, episodes of war, and epidemics to future research, we hypothesize that the findings in this paper point to the potential usefulness of machine learning, shrinkage, and variable selection methods during recessions, as well as to the usefulness of the hybrid models that we introduce. [ABSTRACT FROM AUTHOR]

Based on a narrative dataset constructed by David and Leigh (A new action-based dataset of fiscal consolidation in latin America and the caribbean, IMF Working paper 18/94, 2018) for annual fiscal consolidation shocks, this paper estimates the dynamic effects of fiscal consolidations on income inequality from Jordá's (Am Econo Rev 95:161–82, (2005)) local projections method for nine South American economies in the 1991–2017 period. By decomposing fiscal shocks, the baseline results suggest that spending-based fiscal consolidations significantly increase the Gini index, while tax-based fiscal consolidations do not show statistically significant effects on income inequality. The Gini index for disposable income rises 2.48% in eight years after a spending-based fiscal adjustment of 1% of GDP. The magnitude of this effect is higher than in most of the previous studies carried out for OECD countries. Our main finding for the impact of spending-based fiscal consolidation on inequality in the medium run is robust when using alternative control variables, lag structures, country samples, and the Cyclically Adjusted Primary Balance strategy for identifying the fiscal shocks. [ABSTRACT FROM AUTHOR]

This paper investigates whether state-owned enterprise (SOE) wage premium exists in China. Our contribution is empirical and twofold. First, previous studies commonly use conventional methods, including OLS and fixed effects model, to identify SOE wage premium. It is unclear if the assumptions of these methods are met and if the evidence from these methods is subject to selection bias. In this paper, we use alternative methods to account for selection bias. The first method explores restrictions on a factor model of unobservables to identify the premium. The second method is the minimum-bias (MB) approach of Millimet and Tchernis (J Appl Econ 28:982–1017, 2013). These methods do not rely on the conventional identification assumptions and thus provide a robust check on evidence obtained from conventional methods. Our results show that significant SOE premium exists, that OLS underestimates the premium in early periods and overestimates it in recent periods, and that fixed effects method underestimates the premium. Second, we utilize data that cover a longer period than studied by previous research and thus provide estimates of the SOE wage premium for an extended period. Our results show that the premium averages at 13% in 1990–1995, 9% in 2002–2007, and 10% in 2009–2017. Our results also show considerable variation in SOE wage premium over time, between industrial sectors and between rural–urban migrant and urban local workers. [ABSTRACT FROM AUTHOR]

Presents a list of manuscripts related to economics that will be published in the future issues of the journal "Empirical Economics."

An overview of the organization and contents of the papers in this collection is provided. This collection of fourteen papers on the econometrics of panel data aims to provide the readers with a select group of contemporary theoretical and applied research topics in panel data analysis. [ABSTRACT FROM AUTHOR]

This paper employs a quantile vector autoregressive approach to compare the extent of connectedness between macroeconomic uncertainty and U.S. real activity in normal and extreme economic and financial conditions. Based on a database ranging from January 1960 to February 2023 and using the methodology of Jurado et al. (Am Econ Rev 105(3):1177–1216, 2015), we derive, first, eight real and financial uncertainty measures based on 134 macroeconomic indicators. Second, we examine the quantile connectedness among the eight estimated macroeconomic uncertainties and real activity. The results indicate that real activity is strongly (weakly) influenced by the extremely high (low) values of the real and financial uncertainty estimates, indicating asymmetric spillover effects of US macroeconomic uncertainties on real economic activity. Among the real and financial uncertainty estimates, the real output uncertainty blocks are the most important transmitters of shocks to real activity under looser economic and financial conditions. However, under tighter economic and financial conditions, higher output and income and stock market uncertainty blocks are the major spillover transmitters of shocks to real activity. Finally, connectedness between macroeconomic uncertainties and real activity exhibits the highest level during the recent COVID-19 pandemic outbreak at various quantiles. [ABSTRACT FROM AUTHOR]

The global dominance of the dollar is unquestionable, but the European Commission is committed to strengthening the role of the euro in international relations. Most of the transactions between countries are paid in US dollars even though the United States does not participate in them. Some argue that the euro could become more powerful if it were given more presence in international trade, in particular, in the energy bill of the Eurozone. With the aim of validating that statement, this paper analyses the cointegrating structure between energy imports to the Euro Area from its main partners and those partners' currency exchange rates to the US dollar. We find that there is a bivariate fractional cointegration relationship between the series in most of the countries considered. [ABSTRACT FROM AUTHOR]

This paper explores the effects of financial development on income disparities when certain control parameters are taken into consideration. The dataset consists of 4373 manufacturing and services firms across the globe over 2011–2020. Income inequality is captured by the gap between capital and labour earnings expressed by two ratios according to firms' total asset valuation and profitability. The explanatory variables are divided into four groups: the indicators of financial development, the ratios of firms' growth in the markets, their level of indebtedness and institutional regulation. The results suggest that financial development exerts a significant effect on the capital-to-labour earnings ratio according to the indicators taken into consideration. Excessive debt tends to worsen this gap, while institutional regulations promoting competition play a significant role in reducing income disparities. The robustness of the results is also checked when the constituent firms are categorised according to their size and their operating region. [ABSTRACT FROM AUTHOR]

In this paper, we analyse the socio-economic determinants of environmental crimes such as those focused on wildfire in Italy using panel data at the regional level. We also investigate the effect of economic downturns on wildfire crime. Using the nonadditive fixed effect quantile panel regression model, it was found that socio-economic factors, such as material deprivation, play an important role in driving wildfire crime. Also, risk factors such as unemployment and income inequality were seen to affect the probability of crime in the same direction. On the other hand, a negative relationship between level of education and wildfire crime was found. The results for business cycle support the conjecture that economic downturns have a significant impact on the probability of environmental crime and that the effect is particularly binding in the southern regions where unemployment and income inequality are greater. We also found evidence of a positive correlation between organised crime and wildfire crime. Once again, the grip of organised crime appears to be stronger in the southern regions. [ABSTRACT FROM AUTHOR]

Decarbonization of economies is seen as a high priority for many countries to reduce the impact of climate change. As such, policy makers need robust and reliable decoupling indicators to assess decarbonization progress. This paper utilizes a regression-based approach to estimate decoupling indicators and identify decoupling states in the transport sector. The proposed method is easy to use, data driven, providing robust and reliable estimates of decoupling elasticities and fits within existing policy frameworks. Analyzing the transport sector for 59 countries from across the world beginning 1970, only 16 are weakly decoupling. Most of these have been identified as being part of a group with sustained economy-wide CO2 reductions. Stronger and localized green transport policy action is needed to meet emissions targets for most countries. [ABSTRACT FROM AUTHOR]

This paper examines the relationship among ecological footprint (EF), electricity consumption, and GDP in China using annual data ranging from 1960 to 2019. However, factors like trade openness, urbanization, and life expectancy might increase EF as ecological distortions are mainly human-induced. This study explores the effect of these variables on the environment, which is captured by EF. Quantile Regression estimates indicate that electricity consumption and real GDP increase environmental degradation, while trade and urbanization reduce EF, allowing for a higher environmental quality. On the other hand, the spectral Granger-causality tests reveal that only urbanization and life expectancy affect environmental degradation over the whole frequency domain. In the current geopolitical scenario, relevant policy implications may be derived. [ABSTRACT FROM AUTHOR]

The relationship between political instability (PI) and economic development has been extensively debated in the social sciences, yielding contrasting empirical results. In this article, we synergise two novel techniques—synthetic control (SC) and matrix completion (MC)—to study the economic effects of PI events on the sub-Saharan African scene. Our identification strategies capture potential spatial and temporal heterogeneities of treatment effects. We show that PI inflicts statistically and economically significant collateral damage, albeit heterogeneous across economies and over time. Notably, the group average treatment effect on the treated (ATT) reveals output shrinkage of approximately 17–20 percentage points. Exploiting the temporal dimension of the two techniques, we find that although output loss persists into the long run, the bulk of the damage is wrecked in the short run. This finding particularly casts doubt on the full economic recovery hypothesis in the near aftermath of a PI episode. Furthermore, we unearth spatial heterogeneities of the effects where we show that the negative effects are disproportionately more pronounced for economies which experience protracted PI episodes. Lastly, our paper demonstrates that while both methods provide reliable counterfactuals, the MC estimator yields significantly better pre-treatment fit in our data than the SC framework. [ABSTRACT FROM AUTHOR]

This paper analyzes the asymmetric effects of monetary policy on the economy. The asymmetric effects of the monetary policy may arise due to the state of the economy, the direction of the shock and the magnitude of the shock. To capture these asymmetric effects, we employed a novel methodology viz nonlinear Local Projections Method. From our analysis for the period from 1996 Q 2 to 2020 Q 1 , it is observed that there is significant asymmetry in the effects of monetary policy on Indian economy. The asymmetric effects are mainly due to the state of the economy (expansion/recession) and the direction of the shock (expansionary shock/contractionary shock). Further, it is observed that the effects of monetary policy on output are stronger during expansion compared to recession and expansionary shocks have stronger effect on inflation compared to contractionary shocks. When both the sign of the shock and the state of the economy are taken together, it is observed that contractionary shocks during expansion are more effective in affecting the real economy while expansionary shocks during recession significantly affect inflation. Compared to large shocks, small monetary shocks are found to be more effective. We conclude by arguing that the effects of monetary policy are significantly asymmetric and using a symmetric framework may lead to inaccurate and misleading conclusions. [ABSTRACT FROM AUTHOR]

To which extent do equity and housing hedge against inflation? Despite the extensive literature, there is only little consensus. This paper presents evidence on this question from the Jordà–Schularick–Taylor Macrohistory Database covering 16 countries from 1870 to 2020. The results depend on the time horizon and period considered. Within a 1-, 5-, and 10-year horizon, housing at least partially hedges against inflation. The nominal return–inflation relation is higher in the post-war period. In the long run, housing hedges excessively in the whole sample and perfectly in the post-war period. Equity provides no hedge within 1 year in the entire period, and the returns tend to decrease with inflation in the post-war period. The hedge improves slightly with a longer time horizon and is perfect in the long run in the post-war period. Thus, housing is at least weakly superior in hedging against inflation. The results are robust to a non-housing consumption price index and an asset price appreciation approach. [ABSTRACT FROM AUTHOR]

Digitization and increased accessibility to recorded music have made revenue-generating activities increasingly tied to live performances. In this context, identifying the full impact of concerts (namely capturing the value of activities that emerge as a consequence of them) is of primary interest to assess the sustainability of the different music ecosystems. This paper analyzes spillover effects from playing live to YouTube video streaming. A sample of 190 artists performing in two international music festivals in years 2016 to 2019 has been selected, and the temporal patterns of online video searches for each one have been collected. Using a regression discontinuity design, results show a discrete jump of the YouTube search index for the average performer in the sample after playing live. Furthermore, there is evidence of a gender-specific effect: female performers experience a greater increase in YouTube searches. Though exploratory, this gender bias is consistent with potential theoretical explanations to be explored. Overall, findings provide causal evidence of the effect of live performances on a related but different market (i.e., recorded music), which underlines how technological disruptions may enable alternative revenue sources for musicians. [ABSTRACT FROM AUTHOR]

The role of the G20 in global governance has been increasingly prominent in the context of the extensive spread of coronavirus disease 2019 and the aggravation of financial risk contagion. Detecting the risk spillovers among the G20 FOREX markets is crucial to maintain financial stability. Therefore, this paper first adopts a multi-scale approach to measure the risk spillovers among the G20 FOREX markets from 2000 to 2022. Furthermore, the key markets, the transmission mechanism, and the dynamic evolution are researched based on the network analysis. We derive the following findings: (1) The magnitude and volatility of the total risk spillover index of the G20 countries are highly associated with extreme global events. (2) The magnitude and volatility of risk spillovers among the G20 countries are asymmetric in the different extreme global events. (3) The key markets in the risk spillover process are identified, and the USA always occupies a core position in the G20 FOREX risk spillover networks. (4) In the core clique, the risk spillover effect is obviously high. In the clique hierarchy, as the risk spillover effect is transmitted downward, the risk spillovers present the decrease trends. (5) The density, transmission, reciprocity, and clustering degrees in the G20 risk spillover network during the COVID-19 period are much higher than that in other periods. [ABSTRACT FROM AUTHOR]

This paper investigates the relationship between the price of oil and real output in the United States in the context of a Markov regime switching, identified, structural GARCH-in-Mean VAR model with copulas. We use the copula method to investigate the nonlinear dependence structure, as well as (upper and lower) tail dependence, between the price of oil and real output growth, and Markov regime switching to account for changing oil price dynamics over the sample period. We find an asymmetric negative dependence structure between oil price and output growth shocks and that oil price uncertainty has a negative and statistically significant effect on real output growth. [ABSTRACT FROM AUTHOR]

This paper investigates the responses of house prices and household credit to monetary policy shocks in Norway, using Bayesian structural VAR models. The analysis indicates that the effect of a monetary policy shock on house prices is large, while the effect on household credit is muted. This is consistent with a relatively small refinancing rate (refinancing rate refers to the share of outstanding mortgages that are refinanced each period due to changes in, for example, house prices or interest rate) of the mortgage stock each quarter. Using monetary policy to guard against financial instability by mitigating property-price movements may prove effective, but trying to mitigate household credit may prove costly in terms of GDP and inflation variation. [ABSTRACT FROM AUTHOR]

This paper attempts to provide new evidence on the indirect cost of neighbourhood crime rates on mental wellbeing of residents. Crime places a heavy burden on the economy, and it receives significant attention from the public. Yet, the connection between crime and health for victims and non-victims is not well captured in the literature. Using spatial methodology, we differentiate the effect on mental wellbeing of residents due to the crime rates in their immediate neighbourhood (local) and crime rates in the surrounding areas (spatial). The main innovation of the paper is to use these crime rates at small geographical level (around 8500 residents) to better translate the changes in crime in the neighbourhoods and their effects on a person's mental wellbeing. This is different to other studies that looked at crime incidences in larger geographical units. Our estimation results show that the increase in local and spatial crime rates against the property negatively affect the mental wellbeing of residents. The negative impact of spatial crime rates against the person is also present and is 6.7 times larger than the effect of property crime rates. [ABSTRACT FROM AUTHOR]

Recent work documents that even though partisan polarization may have detrimental economic and social outcomes, polarized societies lead to better governance and less corruption. However, the effect of corruption on partisan polarization has been mostly ignored by the literature. By using various measures of partisan polarization and corruption, this paper demonstrates that corrupt behaviours are associated with more partisan polarization in the European Union, indicating that a stronger presence of corruption leads to higher partisan polarization. The findings are robust to the use of different polarization measures, methodologies, and a battery of control variables. This paper's main finding, increased corruption leading to increased partisan polarization, provides another important mechanism beyond the standard socio-economic factors that led to the current rise in support of parties opposing to European Union and rise of populist parties in European Union. Polarized societies tend to generate inefficient economic outcomes and the alleviation of corruption could improve economic outcomes by decreasing partisan polarization. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the relationship between oil price volatility and US real stock returns using a multivariate framework in which a structural vector autoregression (SVAR) is modified to accommodate the effects of stochastic volatility (SV) in oil prices on stock returns. Our measure of oil price volatility is the conditional variance of the oil price change forecast error. We isolate the effects of volatility in the change in the price of oil on real stock returns and calculate the dynamic responses of stock returns to a shock to oil price volatility. We find evidence that increased oil price volatility has a negative effect on US real stock returns. We support our evidence with the transmission mechanism that details on how the effects of oil price volatility shocks might be channeled into the stock market. Our results remain unchanged in the context of the disaggregate returns for a number of industry portfolios, suggesting that investors should consider oil price volatility in addition to other potential factors that affect stock returns. [ABSTRACT FROM AUTHOR]

This paper estimates the spillover effects of collaboration networks by quantifying the impact of collaborator quantity and quality on research productivity in cardiovascular medicine. Given the endogeneity of coauthor networks, we propose a two-stage approach for identifying spillover effects. The first stage analyzes the influencing factors in a scientist's choice of collaborators. The second stage utilizes characteristics of the predicted collaborators from the first stage to construct instruments for key features of a scientist's actual collaborator networks. Our results reveal that, after controlling for researcher fixed effects, the productivity of prior collaborators is no longer a significant determinant of a researcher's own productivity, while the quantity of previous collaborators remains significant. Moreover, the magnitude of the spillover effects of possessing more collaborators varies by researcher characteristics. [ABSTRACT FROM AUTHOR]

The paper estimates dynamic effects of pandemics on GDP per capita with local projections, controlling for the effects of wars and weather conditions, using a novel dataset that covers 33 countries and stretches back to the thirteenth century. On average, pandemics are found to have prolonged and highly statistically significant effects on GDP per capita—a pandemic killing 1% of the population tends to increase GDP per capita by approx. 0.3% after about 20 years. The study of a more detailed dataset available for the UK reveals that this results mainly from an increase in per capita land and a disproportionate impact of pandemics on low-productivity workers, while monetary expansion, institutional change and innovation could also play some role. At the same time, the effects of pandemics are found to vary with scale and across time and countries, with positive effects present following the Black Death and the Spanish flu pandemics, especially in Northern Europe. This suggests that only the largest and most unexpected pandemics have a positive impact on income. [ABSTRACT FROM AUTHOR]

In this paper, we empirically examine the relationship between the novel macroeconomic attention indices (MAI) and commodity market volatility. In-sample analysis indicates that MAI contribute significantly to the volatility fluctuations in commodity markets. In addition, we employ dimension reduction techniques, shrinkage methods, and combination models in an out-of-sample exercise to assess the predictive ability of MAI, alongside a variety of economic predictors including uncertainty measures, and global as well as US economic indicators. Our empirical results demonstrate the superior predictive ability of the elastic net and LASSO models incorporating MAI together with macroeconomic and uncertainty indicators. This empirical finding is reinforced through a series of robustness checks. However, dimension reduction methods exhibit superior performance in longer forecast horizons. Finally, MAI are more informative for commodity volatility forecasting during economic expansions and non-crisis periods. Our study offers new insights on commodity volatility forecasting. [ABSTRACT FROM AUTHOR]

This paper aims to evaluate how changing patterns of sectoral gender segregation play a role in accounting for women's employment contracts and wages in the UK between 2005 and 2020. We then study wage differentials in gender-specific dominated sectors. We found that the propensity of women to be distributed differently across sectors is a major factor contributing to explaining the differences in wages and contract opportunities. Hence, the disproportion of women in female-dominated sectors implies contractual features and lower wages typical of that sector, on average, for all workers. This difference is primarily explained by "persistent discriminatory constraints", while human capital-related characteristics play a minor role. However, wage differentials would shrink if workers had the same potential and residual wages as men in male-dominated sectors. Moreover, this does not happen at the top of the wage distribution, where wage differentials among women working in female-dominated sectors are always more pronounced than those among men. [ABSTRACT FROM AUTHOR]

This paper focuses on financial asset return spillovers and economic policy uncertainty spillovers in three continents (Europe, America, and Asia) in the last few decades. We examine three financial asset markets (stock, bond, and foreign exchange). Spillovers are measured using the Diebold–Yilmaz spillover index. In the first part, we measure the size of spillovers and find a significant increase in spillovers during the global financial crisis, the European sovereign crisis, and the recent pandemic. In the second part, we test for the effect of uncertainty spillovers on financial asset return spillovers. Using rolling impulse response functions, we obtain the following results: First, the responses of financial markets spillovers to uncertainty spillovers are time-varying and are mostly positive. Second, the highest responses in financial market return spillovers to uncertainty spillovers occur in America and the smallest responses in financial market return spillovers occur in Europe. Third, among the three financial markets, the highest responses apply to the foreign exchange market. Finally, the largest responses during the pandemic apply in Europe. [ABSTRACT FROM AUTHOR]

Lease accounting has often been criticized for being too reliant on bright lines and subjective judgments, as lessees were not required to disclose assets and liabilities arising from operating leases directly on the balance sheet, thereby improving the appearance of the financial condition to investors. To remedy this, in January and February 2016 the IASB and the FASB issued the new accounting standard IFRS 16 and ASC 842, starting a new era of lease accounting and ending the guesswork previously required when calculating companies' lease obligations. This paper investigates the impact on investors' risk perception level of EU and US airline companies, following the enactment of these accounting standards. Results confirm the importance of disclosing all the relevant information about leases directly within the financial statements and not in footnotes, as this increases transparency and comparability between financial statements, protecting all investors, ranging from the rational ones to the more credulous. [ABSTRACT FROM AUTHOR]

This paper provides the first estimates of intergenerational earnings mobility in Chile using administrative data linking parents' and children's earnings from the formal private sector. We calculate mobility measures across the earnings distribution, revealing high mobility in the bottom 80% and 65% of the parents' and children's distribution, respectively. However, we observe significant persistence in the upper tail of the earnings distribution. Additionally, we identify notable gender heterogeneities in these mobility patterns. Specifically, the intergenerational mobility gender gap shows a nonlinear relationship with respect to parental earnings. Furthermore, we find that differences in mobility between the upper tail of the earnings distribution and the rest of the population are more pronounced for daughters than for sons. These findings suggest that the dynamics of gender-based mobility at the upper tail of the earnings distribution differ from those observed in the rest of the population. [ABSTRACT FROM AUTHOR]

The objective of the paper is to understand the role of workers' bargaining for the labor share in transition economies. We rely on a share-capital schedule, whereby workers' bargaining power is represented as a move off the schedule. Quantitative indicators of bargaining power are supplemented with self-constructed qualitative indices derived from textual information describing the legal environment enabling bargaining in each country. Due to multiple data constraints, we employ a cross-sectional empirical model estimated using instrumental variables (IV) methods, where former unionization rates and the time since the adoption of the ILO Collective Bargaining Convention serve as instruments. The sample comprises 23 industrial branches across 69 countries, including 28 transition economies. In general, we find the stronger bargaining power to influence higher labor share, when the former is measured either quantitatively or qualitatively. Conversely, higher bargaining power is associated with a lower labor share in transition economies. This is likely a matter of delayed response to wage pushes, a function of the structural transformation of transition economies, and reconciled with the increasing role of MNCs which did not confront the workers' power rise per se, but introduced automation and changed market structure amid labor market flexibilization, which eventually deferred bargaining power's positive effect on labor share. [ABSTRACT FROM AUTHOR]

This paper examines whether or not public support for climate change mitigation policy can be affected by salient events such as natural disasters. We test this hypothesis using detailed, county-level data from the 2018 Yale Climate Opinion Maps, which documents both the degree to which residents of a county support climate change policy. We show that while natural disasters lead to statistically significant increases in both the share of a county's population that support climate change mitigation policy and/or believe that climate change is happening, the magnitude of these estimated effects are economically small and perhaps not robust to hidden bias. As a result, and even assuming our results are in fact causal, the magnitude of our findings suggest that support as a policy objective by targeting agent's beliefs about the risks climate change poses may ultimately be an ineffectual approach at achieving policymakers' goals. [ABSTRACT FROM AUTHOR]

This paper examines whether Euro Area countries would have faced a more favorable inflation output variability tradeoff without the Euro. We provide evidence supporting this claim for the periods of the Great Recession and the Sovereign Debt Crisis. The deterioration of the tradeoff becomes insignificant only after Draghi's 'whatever it takes' announcement. Results show that the detrimental effect of the Euro is more severe for peripheral countries. We base our results on a novel empirical strategy that, consistent with monetary theory, models the joint determination of the variability of inflation and output conditional on structural supply and demand shocks. [ABSTRACT FROM AUTHOR]

This paper presents alternative unemployment statistics for China, encompassing the extended unemployment rate (U5), which incorporates marginally attached workers, and the nonemployment index (NEI) proposed in recent literature (Hornstein et al. in Econ Q 100(1):1–21). The analysis spans from 1988 to 2021, merging recent data (2012–2018 and 2018–2021) with early estimates (1988–2009). Our findings indicate that both standard and alternative unemployment statistics reveal similar trends in China: a rise in the labor force participation rate and a decline in the unemployment rate since 2012, marking a reversal from the trend before 2009. Additionally, unemployment measures in China align more closely with those of affluent countries from 2007 to 2018 and with less affluent countries from 2018 onwards. Moreover, U5 demonstrates enhanced predictive capabilities for wage dynamics in China's labor market during the recent 2012–2018 period. Lastly, we delve into the discussion of errors in labor market status data. [ABSTRACT FROM AUTHOR]

In this paper, a new measure for uncertainty that affects the economy is proposed, constructed, and applied to an emerging economy, Türkiye. We have constructed an index of economic country-specific uncertainty (ECSU) that is in line with the methodology used in constructing economic policy uncertainty indexes. As the economic uncertainty is of the Knightian type, the essence of measuring it lies in counting the frequency of joint appearances of words related to economics and uncertainty in Turkish-language newspapers. The uncertainty index constructed using local language sources- Turkish performs significantly better in measuring country-specific uncertainty in Türkiye. However, some indexes use English language sources to measure uncertainty in Türkiye- did not make them country-specific. The ECSU was tested by evaluating the dynamic real effects of the uncertainty. This evaluation was performed by the analysis of impulse responses from uncertainty to some economic variables in a vector autoregressive model describing the economy of Türkiye. We find that an unexpected increase in uncertainty in the Turkish-language press is related to decreases in industrial production, employment, and trade. If the uncertainty measure is based on the articles from the English-language press only, no such relationship can be confirmed. We also find that an increase in uncertainty leads to increase in inflation and stock and oil prices. [ABSTRACT FROM AUTHOR]

This paper proposes a panel Granger causality approach for heterogeneous panels with cross-sectional dependence. We define a panel VAR model with unobserved common factors and apply the PANIC procedure to obtain the de-factored data. We then estimate the lag augmented (LA)-VAR model for each cross section and construct the panel statistics based on the meta-analytic approach that combines the p-values of the individual statistics. The Monte Carlo simulations indicate that the combination tests show good size and power properties and appear suitable for the panels where cross sections may have different unit root or co-integration properties. We finally re-investigate Granger causality between export and economic growth in OECD countries. The results shed light on the importance of accounting for cross-sectional dependence within a factor model framework in determining direction of Granger causality for country-specific analysis. The results further reveal that export and economic growth do not cause each other in the majority of the European Union countries. [ABSTRACT FROM AUTHOR]

In this paper, we study the asymmetric effects of different types of capital-embodied technological change, as proxied by tangible and intangible assets, on relative wages (high- to medium-skilled, high- to low-skilled and medium- to low-skilled workers), relying upon the technology-skill complementarity and polarization of the labor force frameworks. We also consider two additional major channels that contribute to shaping wage differentials: globalization (in terms of trade openness and global value chains participation) and labor market institutions. The empirical analysis is carried out using a panel dataset comprising 17 mostly advanced European economies and 5 industries, with annual observations spanning the period 2008–2017. Our findings suggest that software and databases—as a proxy for intangible technologies—exert downward pressure on low-skilled wages, while robotics is associated with a polarization of the wage distribution at the expense of middle-skilled labor. Additionally, less-skilled workers' relative wages are negatively affected by trade openness and global value chain participation, but positively influenced by sector-specific labor market regulations. [ABSTRACT FROM AUTHOR]

Motivated by the increasing demand for alternative assets that can contribute to reducing portfolio risk, this paper examines the volatility spillovers between collateralized loan obligations (CLOs) and various in-demand investment instruments, including equities, bonds, crude oil, commodities, gold, bitcoin, shipping and real estate. The applied methodology comprehends the time-varying parameter vector autoregressive (TVP-VAR) modification of the classical spillover approach, for the period from January 1, 2012, to August 31, 2023. The empirical findings show moderate levels of dynamic connectedness; albeit several external shocks strengthened the interconnection among the assets. Moreover, we compare the ability of CLOs for hedging, during the overall sample period and multiple subperiods, by estimating hedge ratios and optimal portfolio weights, in order to inform investors about feasible portfolio adjustments. Our results indicate that CLOs constitute an effective hedging tool, irrespective of the period covered, as the short position in their volatility provides high hedging effectiveness for investors holding long positions in the volatility of all the remaining assets. [ABSTRACT FROM AUTHOR]

The debate about the impact of robots on employment has been lively. In this paper, I examine the effect of robots on local labor demand in South Korea, one of the most technologically advanced countries in terms of robotics. Using the regional variation in robot exposure constructed from national industry-level robot adoption data and the initial distribution of industrial employment in cities, I find that robots did not reduce local labor demand. However, I estimate declines in labor demand in the manufacturing sector and routine jobs. An increase in one robot per 1000 workers in terms of exposure to robots is correlated with a decline in the job vacancy growth rate of 2.6%p in the manufacturing sector and of 2.5%p in routine jobs. No significant relationship is found between robot exposure and labor demand in the service sector or non-routine jobs. [ABSTRACT FROM AUTHOR]

This paper applies causal machine learning methods to analyze the heterogeneous regional impacts of monetary policy in China. The methods uncover the heterogeneous monetary policy impacts on the provincial figures for real GDP growth, CPI inflation, and loan growth compared to the national averages. The varying effects of expansionary and contractionary monetary policy phases on Chinese provinces are highlighted and explained. Subsequently, applying interpretable machine learning, the empirical results show that the credit channel is the main channel affecting the regional impacts of monetary policy. An imminent conclusion of the uneven provincial responses to the "one-size-fits-all" monetary policy is that different policymakers should coordinate their efforts to search for the optimal fiscal and monetary policy mix. [ABSTRACT FROM AUTHOR]

In this paper, we propose a hybrid Watts-MPI multidimensional poverty measure that combines the multidimensional Watts poverty index (MWPI), which can accommodate continuous poverty dimensions, with the multidimensional poverty index (MPI), which can accommodate binary poverty dimensions. Unlike the stand-alone MPI that entails total loss of dimension-specific information on both poverty intensity with respect to shortfall and inequality, the proposed hybrid Watts-MPI measure entails only partial loss of such information since poverty intensity and inequality estimates can still be obtained for the continuous poverty dimensions included in the hybrid measure. The hybrid Watts-MPI also specializes to the stand-alone MWPI and MPI when all the poverty dimensions are continuous and binary, respectively. Furthermore, formation of the hybrid Watts-MPI does not entail loss of normative properties by either the constituent MWPI or MPI. The seemingly unrelated regression approach to the estimation of the hybrid Watts-MPI is described and an empirical example demonstrating its efficacy is provided. [ABSTRACT FROM AUTHOR]

This paper explores a joint test of predictability and one-time structural break, both of which are assumed to be absent under the null hypothesis. The test combines IVX estimator with a sup-Wald-type statistic. The limiting distribution of the test statistic is expected to be non-pivotal under (near-)integration. Nevertheless, for univariate cases, the distribution is highly insensitive to the variation of unestimable nuisance parameter. We hence propose to use critical values from the pivotal distribution derived under stationarity for empirical study. Simulation results suggest that this approach delivers satisfactory and robust inference in finite sample. An empirical application to the predictability of US stock returns is provided. [ABSTRACT FROM AUTHOR]

The literature on the estimation of treatment effects has matured in economics. The potential outcomes framework guides the estimation of the causal effect of economic choices or policy interventions. The application of methods from the treatment effects literature has spread from the analysis of the effects of labor market programs and the wage return to education to other areas in economics. This special issue involves methodological developments and state-of-the art applications of methods to estimate treatment effects in various areas of economics. The contributions illustrate the emphasis within the treatment effects literature on the separate but related issues of heterogeneous treatment effects and identification. The careful, high-quality substantive applications collected here show just how much applied work on policy-relevant topics has benefitted from the methodological developments in the treatment effects literature. At the same time, many of the substantive papers make important methodological contributions as well. [ABSTRACT FROM AUTHOR]

This paper compares multipliers of different categories of US federal government spending, and in doing so provides a new insight as to why fiscal multipliers may differ across countries and time. We identify exogenous federal government spending shocks at the state level for defense and non-defense spending. Using a projection-based approach, we estimate the cumulative multiplier due to shocks in either of these spending categories. Our results indicate that defense spending yields lower multipliers than non-defense spending. Thus, focusing only on defense spending may result in underestimating the multiplier for government spending. [ABSTRACT FROM AUTHOR]

This paper examines whether reported income generates biases for studies on economic mobility and poverty dynamics. Using a linear measurement error model capturing mean-reverting measurement error, this study finds that substantial classical measurement error exists in reported data, leading to a bias toward zero in the estimate of income dynamics. Time-invariant non-classical measurement error and unobserved heterogeneity offset the effect of classical measurement error. This study also identifies the standard deviation of the measurement error, which is estimated to be about 70% of that of the equation error in the income model, suggesting that random measurement error is substantial. [ABSTRACT FROM AUTHOR]