Search

This paper examines North American pulp and paper company bankruptcies that occurred between 1990 and 2009. We demonstrate that shareholders suffer substantial losses (37 %) during the month a bankruptcy occurs. Encouragingly, we show that financial ratios are useful in predicting firm failure and that failed firms are less profitable, more liquidity constrained and higher in debt leverage. Using a binary logit model in the spirit of Ohlson (J Acc Res, 19, 109–131, 1980 ), we predict financial distress for pulp and paper firms 1 to 2 years ahead of the bankruptcy. We also adapt and re-estimate the empirical model on a sample of pulp and paper firms and perform in-sample and out-of-sample forecasts. For the out-of-sample analysis, our re-estimated Ohlson models correctly predict 93 % of bankruptcy and non-bankruptcy outcomes. [ABSTRACT FROM AUTHOR]

In this paper, we study the transmission and effectiveness of the public expenditure shock across business cycle phases in the Indian economy. The empirical results suggest that the deflationary impact of the public expenditure shock and the subsequent accommodative response of interest rates exhibit a countercyclical public expenditure multiplier during the contraction period. Moreover, the large and significant negative impact of the public expenditure shock on inflation and the interest rate has resulted in a larger public expenditure multiplier during a supply-side recession than a demand-side recession. Based on empirical evidence, we suggest that policymakers consider the presence of nonlinearities in the transmission and effectiveness of the public expenditure shock while taking fiscal policy measures. [ABSTRACT FROM AUTHOR]

Papers in economics often try to find the 'best' estimate of a parameter. If researchers behave as predicted by economic theory, the research process can be modeled and simulated. The 'best' estimate is selected from $$J$$ regression experiments by a selection rule, SR, which gives the researcher's preferences for the fit (significance) and size of the estimated parameter. Eight $$J$$ s and five SRs are considered. To find a stable pattern for all 40 cases, 70 million regressions are simulated. The key results are: (1) All rational SRs cause the selected estimate to be substantially biased in the direction of the priors of the researcher. (2) All such rules give almost the same bias. It can be assessed from a set of estimates, and (3) the standard PET estimate of the meta-average reduces the bias by more than 90 %. [ABSTRACT FROM AUTHOR]

The process of trade liberalization is also a process of deepening and improving China's institutions, which will certainly have a profound impact on social trust, but literature on how trade liberalization affects trust is scarce. This paper examines the impact of import trade liberalization on Chinese residents' social trust using a fixed-order regression model based on the Chinese General Social Survey (CGSS) data from 2010 to 2017. The study finds that import trade liberalization significantly contributes to the enhancement of social trust among Chinese residents. The mechanism analysis confirms that import trade liberalization enhances the social trust of Chinese residents mainly through the channel of improving institutional quality. Heterogeneity analysis shows that different sensitivities to institutions of heterogeneous individuals lead to a more significant contribution of import trade liberalization to residents' social trust levels in highly institutionalized regions, party and government organs, the military, non-agricultural households, and higher educated groups of residents. The findings of this paper imply that building an all-around opening pattern in the new era can contribute to the enhancement of mutual trust in Chinese society. [ABSTRACT FROM AUTHOR]

Standard two-stage least squares (2SLS) regression remains dominant in instrumental variables estimation of causal effects even though the literature has shown that 2SLS may be inconsistent when effects are heterogenous and the instrument is only valid when conditioning on covariates. To show that this is not merely a hypothetical threat, this paper re-estimates the returns to college using college proximity as an instrument based on the data from Card (Aspects of labour market behavior: essays in honour of John Vanderkamp, University of Toronto Press, Toronto, 1995). The results show that 2SLS yields systematically larger estimates of the returns to college than more flexible estimators based on the instrument propensity score. In the full sample, differences amount to about 50 to 100%. This is due to the implicit conditional-variance weighting performed by 2SLS. Moreover, in line with the theoretical prediction by Sloczynski (When should we (not) interpret linear IV estimands as LATE? IZA discussion papers 14349, Institute of Labor Economics (IZA), 2021), findings suggest that the impact of the conditional-variance weighting is larger when instrument groups are not roughly the same size. Thus, it is advised to use 2SLS with caution and use estimators based on the instrument propensity score instead when groups are of different size and covariates are predictive of the instrument. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic proved to be an unprecedented socio-economic crisis in the last decades. More than three years after its outbreak, there is still uncertainty regarding its future evolution. National and international authorities adopted a prompt and synchronized response to limit the adverse effects of the health crisis, in terms of socio-economic damage. Against this background, this paper assesses the efficiency of the measures implemented by fiscal authorities in selected Central and Eastern European countries to ameliorate the economic repercussions of the crisis. The analysis reveals that the impact of expenditure-side measures is stronger than that of revenue-side ones. Additionally, the results of a time-varying parameter model indicate that the fiscal multipliers are higher in times of crisis. In view of the ongoing war in Ukraine, the related geopolitical turmoil and energy crisis, the findings of this paper are especially pertinent, given the need for additional fiscal support. [ABSTRACT FROM AUTHOR]

This paper studies spouses' intrahousehold decision-making, using unique information from the European Union Statistics on Income and Living Conditions special module on Intrahousehold Sharing of Resources. We build an index to measure the bargaining power of the wife in household decision-making in European countries and analyze how that index correlates with household demographic characteristics. We find cross-country differences in the values of this index, although estimates show that, in general, older, relatively more educated and working spouses with higher wages, have more power in intrahousehold decision-making. Furthermore, country-level conditions correlate with spouses' bargaining power in household decision-making. The paper provides a direct empirical exploration of intrahousehold decision-making in a cross-country setting. [ABSTRACT FROM AUTHOR]

This paper examines the short- and medium-run effects of U.S. federal personal income and corporate income tax cuts on a wide array of economic policy variables in a data-rich environment. Using a panel of U.S. macroeconomic data set, made up of 132 quarterly macroeconomic series for 1959–2018, we estimate factor-augmented vector autoregression (FAVARs) models where an extended narrative tax changes dataset combined with unobserved factors. The narrative approach classifies if tax changes are exogenous or endogenous. This paper identifies narrative tax shocks in the vector autoregression model using the sign restrictions with the Uhlig's (J Monet Econ 52(2):381–419, 2005. https://doi.org/10.1016/j.jmoneco.2004.05.007) penalty function. Empirical findings show a significant expansionary effect of tax cuts on the macroeconomic variables. Cuts in personal and corporate income taxes cause a rise in output, investment, employment, and consumption; however, the effects of corporate tax cuts have relatively smaller effects on output and consumption but show immediate and higher effects on fixed investment and price levels. We validate the model's specification and the identification of tax shocks through a reliability test based on the Median-Target method. Additionally, sensitivity analysis employing the local projection vector autoregression model, number of iterations of the algorithm, and incorporating diverse factor specifications reaffirms tax cuts' persistent and expansionary effects. Our contribution to the narrative tax literature lies in providing empirical evidence that aligns with the notion that reductions in personal taxes demonstrate a higher efficacy as a fiscal policy tool when compared to reductions in corporate income taxes. [ABSTRACT FROM AUTHOR]

This paper provides a novel dataset of time-varying measures on the degree of countercyclicality of fiscal policies for advanced and developing economies between 1980 and 2021. The use of time-varying measures of fiscal stabilization, with special attention to potential endogeneity issues, overcomes the major limitation of previous studies and allows the analysis to account for both country-specific as well as global factors. The paper also examines the key determinants of countercyclicality of fiscal policy with a focus on factors as severe crises, informality, financial development and governance. Empirical results show that (i) fiscal policy tends to be more countercyclical during severe crises than typical recessions, especially for advanced economies; (ii) fiscal countercyclicality has increased over time for many economies over the last two decades; (iii) discretionary and automatic countercyclicality are both strong in advanced economies but acyclical (at times procyclical) in low-income countries; (iv) fiscal countercyclicality operates primarily through the expenditure channel, particularly for social benefits; and (v) better financial development, larger government size and stronger institutional quality are associated with larger countercyclical effects of fiscal policy. Our results are robust to various specifications and endogeneity checks. [ABSTRACT FROM AUTHOR]

The traditional applied demand system estimation assumes that when consumer income and commodity prices change, the consumers instantaneously fully adjust to a new consumption equilibrium level and use a static demand system such as Static Linear Almost Ideal Demand System (Static LA-AIDS) for estimation. However, in real-life situations, such an assumption does not hold as consumers take time to settle to a new consumption equilibrium level. Hence, dynamic demand system estimations generate more nuanced insights into the short-run dynamics of consumer demand. This paper estimates two forms of dynamic versions of AIDS, Dynamic LA-AIDS and the error-corrected LA-AIDS, and compares the results with the Static LA-AIDS. The paper also models the consumption patterns of consumers in developed and developing countries and provides a comparative analysis of implied elasticities using recent data. The results show that the dynamic models support demand theory hypotheses—demand homogeneity and Slutsky symmetry—more than the static model. The estimated mean own-price elasticities reveal that the demand in the short-run and long-run is price inelastic across all countries. Long-run and short-run income elasticities demonstrated notable variation across various commodity groups and country groups. For example, the restaurant meal is a luxury in the short-run for all countries. In the long-run, it is a necessity in developed countries and a luxury in developing countries. Food and housing are necessities; durables, transport and recreation are luxuries in developed and developing countries in the long-run and short-run. [ABSTRACT FROM AUTHOR]

In response to the beginnings of the COVID-19 pandemic, India's government instituted a severe nationwide lockdown in late March 2020. In this paper, we analyze household survey data on income from an Indian state, Punjab. We analyze the impacts of the pandemic and lockdown on total household income, as well as its components, including wages, business income and transfers. This paper innovates in this area by using Poisson Pseudo Maximum Likelihood estimation to deal with the skewed distributions of various income components, as well as quantile regressions to examine differential impacts across the income distribution. We examine the differences between rural and urban households, differential impacts on female-headed and laborer households, and the time pattern of impacts. We find that rural households experienced more persistent income declines than urban households, and their wages suffered relatively more. Households with daily laborers were most badly affected, and this was especially true at the bottom of the income distribution. [ABSTRACT FROM AUTHOR]

In this paper, we propose a methodology to identify relationships between web data and social/economic variables, such as inflation. Our method enables the selection of relevant time series from a large data sample by employing a criterion based on a few hypotheses regarding their dynamics. Specifically, we examine the correlation between web activities and the dynamics of two macroeconomic variables: the unemployment rate and US automotive sales. We demonstrate how changes in the search volume of specific keywords, as measured by corresponding Google Trends data, are reflected in the underlying dynamics of these variables. The findings presented in this paper, along with the versatility of our approach, suggest the potential extension of this study to other economic variables. [ABSTRACT FROM AUTHOR]

This paper investigates the role of hysteresis in the long-term transmission of consolidations in a panel of 17 OECD countries. The evidence supports that the hysteresis of the labour market is the main driver of consolidations' long-term effects: an increase in the rigidity of the labour market exacerbates and prolongs the contraction following tax-based consolidations, while it mutes the expansion following expenditure-based consolidations. In contrast, the response of productivity is irrelevant to the presence of the long-term scars. [ABSTRACT FROM AUTHOR]

This short note honors Ingmar Prucha’s many scientific contributions in econometrics and empirical economics. We conclude with a few more personal remarks. [ABSTRACT FROM AUTHOR]

This paper proposes an inference procedure for the interactive fixed effects model that is valid in the presence of cross-sectional dependence. When the error terms are cross-sectionally dependent, the least square (LS) estimator of this model is asymptotically biased and therefore the associated confidence interval tends to have a large coverage error. To address this, we propose a bias correction of the LS estimator and a cross-sectional dependence robust variance estimator to construct associated test statistics. The paper also discusses practical issues in implementing the proposed method, including the construction of distance that reflects the decaying pattern of cross-sectional dependence and the selection of the bandwidth parameters. Monte Carlo simulations show our procedure works well in finite samples. As empirical illustrations, we apply our procedure to study the effect of divorce law reforms on divorce rates and the impact of clean water and sewerage interventions on child mortality. [ABSTRACT FROM AUTHOR]

Since the seminal paper of Nelson and Plosser (J Monet Econ 10(2):139–162, 1982), analyzing the nature of shocks to macroeconomic and financial data has attracted great attention and it continues to be up-to-date, especially, in conjunction with the advances in unit root literature. This paper examines the persistence in macroeconomic and financial variables for Turkey by means of the recent developments in the quantile autoregression models to account for non-normal distributions, structural changes, and asymmetric dynamics. The results show that while the conventional unit root approaches fail to reject the null hypothesis of unit root for most the of 30 macroeconomic and financial time series, the nonlinear quantile unit root test with smooth structural changes supports evidence on a stable long-run equilibrium for 23 variables. It further reveals asymmetric persistence in most of the Turkey's macroeconomic and financial data, implying that the effect of an economic shock in inflationary state is different than that in recessionary state. [ABSTRACT FROM AUTHOR]

This paper (re-)evaluates the effectiveness of central bank asset purchases in the euro area given their prominent role in the ECB's response to the pandemic as well as the evidence from the US suggesting diminishing returns of this policy measure over time. We analyse their macroeconomic impact in the euro area using a time-varying parameter structural vector autoregression with stochastic volatility and perform identification via sign and zero restrictions of Arias et al. (Econometrica 86:658–720, 2018), their fusion with high-frequency information approach akin to Jarociński and Karadi (Am Econ Macroecon 12:1–43, 2020) and a novel method which merges high-frequency identification with narrative sign restrictions of Antonlin-Diaz and Rubio-Ramirez (Am Econ Rev 108:2802–2829, 2018). We find that the potency of the ECB's asset purchases to lift inflation has indeed considerably declined over time with several factors contributing to a more muted response of prices to central bank asset purchases. Our results show that the reanchoring channel is no longer active while the counterproductive effects via the mechanism outlined in Boehl et al. (Working Paper No. 691, 2020), which we dub the capacity utilization channel, have emerged lately and are further complemented with disinflationary effects stemming from the cost channel. Also, the effects passed through more standard transmission channels of central bank asset purchases like portfolio rebalancing and signalling, while still significant, appear to be less persistent recently. Overall, our findings point to a diminishing return of the ECB's asset purchases to stabilize inflation and its expectations in the euro area. [ABSTRACT FROM AUTHOR]

The frequent price volatility in China's agricultural futures market has aroused concern about price bubbles in the agricultural futures market. This paper analyzes the characteristics of price bubbles in China's agricultural futures market by using data from nine active agricultural commodities futures and the Nanhua agricultural price index. The empirical results show that only soybean futures, sugar futures, cotton futures, and the Nanhua agricultural price index exist price bubbles. The duration of price bubble accounts for 2.5–6.2% of the whole sample interval. Moreover, combined with China's agricultural policy, this paper finds that after 2014, China's policy reform from the "yellow box" policy to the "green box" policy and the "blue box" policy can inhibit price bubbles of agricultural futures market to a certain extent. Additionally, the higher the dependence on the international market, the higher the risk of price bubbles in the agricultural futures market. Besides, agricultural futures are more prone to price bubbles with long duration and large price change during the agricultural crisis (soybean and cotton experienced price bubbles from 2007 to 2008 and 2010 to 2011, respectively). The findings of this paper have important policy implications for policy-makers. [ABSTRACT FROM AUTHOR]

This paper estimates a panel model in which the relationship between trade and government size is determined by countries' per capita GDP. The panel model covers 126 countries during the 1980–2018 period. Estimates of the model show that the correlation between trade and government size is decreasing in the level of countries' per capita GDP. For high-income countries with a per capita GDP above $12000US, the association between trade and government size is negative. For low-income countries with a per capita GDP below $1000US, the relationship between trade and government size is positive. In the year 2018, the average country had a per capita GDP of about $14228US. For this country, the estimated coefficients suggest that a 1% increase in trade had a predicted association with the long-run level of the size of government of over 0.17%. The paper also presents estimates suggesting that the relationship between trade and the composition of government spending differs depending on countries' incomes. [ABSTRACT FROM AUTHOR]

Based on the first batch of smart city pilots in China, this paper systematically investigates the impact of smart city construction on urban employment and employment structure, and its influence mechanism and urban heterogeneity are explored using the difference-in-differences (DID) model. The main conclusions are as follows: (1) Smart city construction significantly promotes urban employment, especially employment in the secondary and tertiary industries. (2) Digital technology development and public services are important mechanisms for smart city construction to improve urban employment. (3) There was heterogeneity among Chinese cities, with the employment promotion effect of smart city construction is primarily reflected in cities located in the eastern and central regions, medium cities, large cities, as well as cities with higher levels of financial development, human capital, and informatization. (4) Through different impacts on various sectors, smart city construction promotes the transfer of employment to the service sector and optimizes the urban employment structure. Conclusions enrich the academic community's understanding of the development and construction of smart cities and provide enlightenment and reference for the formulation and promulgation of relevant supporting policies. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemics and the lockdowns imposed to mitigate the rise of infections beyond manageable levels strongly affected international trade. Although the health crisis and the mobility restrictions associated with lockdowns are closely related, their impacts on international trade have a different nature. This paper uses monthly firm-level trade data for Portuguese firms to measure the impact of partner countries' lockdowns on nominal export and import flows during 2020 and the first half of 2021, while also assessing the impact of the health crisis. The high time frequency and granularity of the data contribute to the identification of the impact of these obstacles on trade. We conclude that the detrimental impact of lockdowns is sizeable and broadly similar in exports and imports, and the impact of the health conditions is slightly stronger in exports. There is evidence that the detrimental impact of lockdowns was stronger for larger firms, for those with higher geographical concentration of trade, more integrated in global value chains and in the upper quartiles of the trade unit value distribution. The negative impact is also estimated to be larger for industries with high import content and for trade partners that are more important as sources of value added to be embodied in Portuguese exports. Results also suggest that exports adapted to the prevailing circumstances as of June 2020, but such an effect is not clear in imports. [ABSTRACT FROM AUTHOR]

This paper uses causal graphs to test for the direction of instantaneous causality between economic policy uncertainty (EPU) and stock market volatility. The paper derives simple test regressions from a causal graph, applies the regressions to data for 23 countries, and shows how causal graphs can be used to examine the robustness of the results. The empirical results imply that stock market volatility is not a cause of EPU and that domestic EPU and US EPU are often instantaneous causes of stock market volatility. A comparison of the graph-based approach with a VAR-based causality analysis demonstrates that both approaches yield consistent statistical results. However, in contrast with the VAR approach, the graph-based approach utilizes the additional information provided by the causal graph to infer the direction of instantaneous causality. [ABSTRACT FROM AUTHOR]

In the literature on the effects of charging user fees for healthcare on health outcomes, Shinsuke Tanaka's 2014 AEJ: Economic Policy paper evaluating South Africa's 1994 user fee reform, "Does Abolishing User Fees Lead to Improved Health Status? Evidence from Post-Apartheid South Africa," is regarded as a seminal piece of evidence demonstrating that eliminating user fees significantly improves population health. Tanaka finds that South Africa's elimination of user fees for pregnant women and young children caused children's weight-for-age z-scores (WAZ) to rise by 0.6, making it one of the most successful child nutrition interventions ever studied. However, evaluations of the same reform employing other methodologies have found that it had little to no effect on outcomes like healthcare utilization, making it difficult to understand how it might have had such large effects on WAZ. In this paper, I replicate, reanalyze, and extend Tanaka, 2014, considering its use of a two-way fixed effects model (TWFE) with additional covariates in the context of recent methods literature exposing the limitations of such designs. I show that Tanaka's approach may not yield an unbiased causal estimate under the intended conditional parallel trends assumption but find that his results are robust to reanalysis with updated estimators. I then explore the implications of substantial treatment effect heterogeneity across subgroups within Tanaka's sample for the external validity of his results, arguing that this heterogeneity severely undermines the case that his results generalize. I thereby recontextualize the debate over the effects of eliminating user fees in South Africa in terms of new thinking about TWFE and treatment effect heterogeneity, illustrating the practical implications of those advances in the process. [ABSTRACT FROM AUTHOR]

The effects of urban transport policies on household welfare are a broadly understudied topic in developing countries. This paper analyzed the distributional effects of a bus rapid transit (BRT) system in Barranquilla, Colombia. Using geocoded household survey data over 2008-15 and a difference in differences approach, it showed that, in proximity to newly opened stations, poor households were replaced by non-poor households. These results suggested that the designers of such systems, despite the generally positive assessment of the systems, may have overlooked distributional consequences. Moreover, it showed that results in studies that do not control for the observed changes will be biased. [ABSTRACT FROM AUTHOR]

Network analysis allows us to introduce different metrics that complement the traditional indicators to measure academic performance, generally based on individual production. In this paper, we show how the use of these techniques provides a more global point of view, introducing indicators that, beyond individual merits, measure the capacity of researchers to generate more intangible assets. We focus on collaboration among groups that can enrich the potential of the research ecosystem as a whole. We present not only numerical indicators, but also several visualisation schemes to see how this approach can help in the academic evaluation and decision-making process of research managers. We have used, as a case study, the research ecosystem formed by more than five thousand economists from Spanish institutions. [ABSTRACT FROM AUTHOR]

This paper investigates the importance of bureaucratic inertia in foreign aid allocation. Inertia puts a limit on the ability of foreign aid to alleviate poverty and promote growth. We exploit the 9/11 attacks as a natural experiment that provides a lower bound on the effects of inertia. We make use of a dynamic panel data model combined to a proper treatment of the sample selection problem inherent to virtually all models on aid decisions. The paper moves beyond existing studies and provides an ordering of the donor's motivations. Interestingly, merit-based motivations have sizable effects on aid decisions. However, inertia is found to drive most of the aid distribution. This may provide a rationale for the weak enforcement of aid contracts. Inertia introduces a time inconsistency problem on the side of the donor. Ex-post, the donor of conditional aid has incentives to deliver it regardless of reforms' implementation or recipient's discipline. Anticipation that this will happen destroys the recipient's incentive to carry out costly policy reforms. This puts the whole aid architecture under strain. Coordination among donor agencies, donors' investment in reputation and institution building as well as changing aid modalities rather than volumes seems to be promising routes toward re-establishing efficiency. [ABSTRACT FROM AUTHOR]

This paper focuses on the spillover dynamics of shocks originating in China during the last two decades. More specifically, the paper compares the effects of a shock to China's GDP and exchange rate using early 2000s trade patterns with those of two decades later. We use a global vector autoregressive (GVAR) model as it allows to consider trade interactions as well as financial linkages through interest rates, stock prices, and exchange rates. Our results indicate that the shock spillovers from China have become more pronounced over the past two decades. While the world has become more exposed to China's economy, it has become more susceptible to Chinese economic shocks. This paper contributes to the literature by evaluating the dynamics of China's spillover effects and highlights the structural changes in trade between major global trade players. [ABSTRACT FROM AUTHOR]

Motivated, in part, by the recent surge of interest in robust inequality measurement, cross-country inequality comparisons, applications of heavy-tailed distributions and the study of global and upper-tail inequality, this paper focuses on robust analysis of heavy-tailedness properties and inequality in the upper tails of income distribution in Russia, as measured, mainly, by its tail indices. The study is based on recently developed approaches to robust inference on the degree of heavy-tailedness and their implications for the analysis of upper-tail inequality discussed in the paper. Among other results, the paper provides robust estimates of heavy-tailedness parameters and tail indices for Russian income distribution and their comparisons with the benchmark values in developed economies reported in the previous literature. The estimates point out to important similarity between heavy-tailedness properties of income distribution and their implications for the analysis of upper-tail income inequality in Russia and those in developed markets. [ABSTRACT FROM AUTHOR]

In light of the growing interest in studying productivity spillovers, Zhao et al. ([18]) extend proxy-variable estimators of nonparametric production functions to the case when technology spillovers and common shocks have persistent effects on firm productivity and are controlled for through spatial networks and a factor structure in the productivity evolution process. The special issue then concludes with a flurry of papers pursing efficiency/productivity analyses in a wide range of empirical contexts which illustrates both the breadth and depth of the productivity literature. Empir Econ. https://doi.org/10.1007/s00181-020-02009-9 6 Battisti M, Belloc F, Del Gatto M (2020) Is the productivity premium of internationalized firms technology-driven? Using their recently developed methodology for unbundling technology and total factor productivity (TFP) by estimating technology-specific production function parameters, Battisti et al. ([6]) ask whether the productivity advantage of internationalized firms documented in the international trade literature can be interpreted most accurately in terms of proximity to the "technological frontier" or pure productivity premiums. [Extracted from the article]

Nowcasting can play a key role in giving policymakers timelier insight to data published with a significant time lag, such as final GDP figures. Currently, there are a plethora of methodologies and approaches for practitioners to choose from. However, there lacks a comprehensive comparison of these disparate approaches in terms of predictive performance and characteristics. This paper addresses that deficiency by examining the performance of 17 different methodologies in nowcasting US quarterly GDP growth, including all the methods most commonly employed in nowcasting, as well as some of the most popular traditional machine learning approaches. Performance was assessed over a 20-year period, from 2002 to 2022. This span encompassed two crises, the 2008 financial crisis and the COVID crisis, as well as extended tranquil periods. The two best-performing methodologies in the analysis were long short-term memory artificial neural networks (LSTM) and Bayesian vector autoregression (Bayesian VAR). To facilitate further application and testing of each of the examined methodologies, an open-source repository containing boilerplate code that can be applied to different datasets is published alongside the paper, available at: github.com/dhopp1/nowcasting_benchmark [ABSTRACT FROM AUTHOR]

In this paper, we study the effects of macroeconomic uncertainty shocks on the US economy in the long-run using an IV-SVAR methodology for the period 1960–2019. Following Piffer and Podstawski (Econ J 128(616):3266–3284, 2018), we use variation in gold prices as an instrument to identify the uncertainty shocks. We find that potential output decreases persistently in response to an uncertainty shock. Furthermore, our study shows that decline in the R &D investments and business dynamism are the two key transmission channels of the uncertainty shocks that generate long lasting effects on the economy. [ABSTRACT FROM AUTHOR]

This paper investigates the impact of exchange rate and exchange rate volatility on export performance by considering technological classification in addition to total exports. The study utilizes a panel SVAR methodology introduced by Pedroni P (2013) Structural panel vars. Econometrics 1(2):180–206. and analyzes panel data covering 58 countries and 48 quarters from the period of 2010Q1 to 2021Q4. Although the results suggest no precise evidence that exchange rate and exchange rate volatility shocks affect total export volumes, they exhibit heterogeneity across countries and vary in terms of technological density. Countries that have more flexible exchange rate policies and use large volumes of imported materials to produce export products demonstrate, on average, higher sensitivity to exchange rate volatility. Additionally, as the share of exports crossing more than one country border in total exports increases, the exposure of export to exchange rate volatility also rises. Countries described as commodity exporters and large energy consumers tend to be less responsive to exchange rate levels in their exports. [ABSTRACT FROM AUTHOR]

This paper attempts to extend the approach of quantitative investment and provide investors with suggestions about volatility timing. Based on the volatility-managed portfolios strategy, we propose two volatility–tail risk-managed portfolios strategies by combining the volatility and tail risk forecasting methods. We subject seven indices in China's stock market to verify the performance of these two strategies. The empirical results show that volatility–tail risk-managed portfolios yield better performance than buy-and-hold portfolios and volatility-managed portfolios in terms of annualized average returns, Sharpe ratio, maximum drawdown and Calmer ratio. Furthermore, we find that the effectiveness also depends on the volatility clustering of portfolios and the selection of investment periods. [ABSTRACT FROM AUTHOR]

Private policing is generally used to curb crime in certain neighbourhoods. The impact of an increase in these services on the city as a whole is unclear, as crime could shift from protected to unprotected targets, causing greater social harm. In practice, estimating this effect at the city level encounters at least two problems. First, the simultaneity between the demand for private policing and criminal activity requires appropriate instrumental variables to mitigate endogeneity biases. Second, the dependent and endogenous variables can have an excessive number of zeros at the same time, requiring the use of more specialized econometric models. In this paper, I combine Clotfelter's theoretical model for private policing and crime with Amemiya's econometric model for simultaneously censored outcomes, linking structural and reduced forms and discussing identification issues. Then, a regular Bitobit is modified to estimate reduced forms with many zeros outcomes in a set of copulas to improve censoring specifications with endogeneity. Finally, I conduct an empirical study examining an exclusive database from Brazil to discuss the copula approach, and the hypothesis that more private policing reduces crime at the city level is not rejected. [ABSTRACT FROM AUTHOR]

This paper revisits the weather effects with a comprehensive examination that includes all eight weather elements after controlling for the effect of seasonal affect disorder using the data from Taiwan between January 1, 1995, and October 31, 2021. We further employ principal component analysis to provide us with components that fittingly represent various multi-facet weather conditions and intuitively depict the relationship between the weather as we know it and investor behavior manifested in the overall market in returns, volatility, turnover, and liquidity. The results from a vector autoregression model based on both the individual weather elements and weather components show that the weather effects exist. We also find that warnings about extreme weather condition of a typhoon have a direct effect and heavy rain an indirect effect on market liquidity. In addition, institutional investors' buying and selling activity is linked to weather conditions. The robustness of the weather effects is further demonstrated by the results of the intraday return analysis and from considering different numbers of weather elements and conditions in the model. [ABSTRACT FROM AUTHOR]

This paper studies how individuals consider other individuals' preferences when selecting whom to include in a group or network in the absence of any personal taste or statistical reason associated with the inclusion of a particular applicant. This type of decision emerges, for instance, when unprejudiced white landlords discriminate against black applicants because of the prejudice of existing white tenants, or when employers hire an employee-referred candidate instead of an outsider who is disfavored by current employees. We investigate the potential causes as to why selectors consider the group composition preferences of other group members. First, selectors have altruistic feelings toward them and select their preferred candidates. Second, selectors anticipate that their cooperativeness depends on who will be included and so strategically select candidates who are preferred by current group members. We investigate the reasons for this type of discrimination in an experiment in which we allow for endogenous group formation and show that discriminatory behavior in embedded contexts emerges even when selectors have no taste for any candidate nor any reason to discriminate statistically, but still discriminate in favor of a current group member's preferred candidate both for altruistic and strategic reasons. We thereby identify a new major source for discrimination and for the perpetuation of systematic exclusion of outsiders disfavored by insiders, even when the latter do not participate in the decision of whom to include. We discuss the implications for policies aimed at overcoming strategic discrimination in hiring decisions, employee referral programs, quotas, and bonus payments. [ABSTRACT FROM AUTHOR]

The reciprocal relationship between psychiatric and substance use disorders is well-known, yet it remains largely unknown whether mental health morbidity causally leads to addictive behaviours. This paper utilises a fixed effects instrumental variables model, which is identified by time-varying sources of plausibly exogenous variations in mental health, and a nationally representative panel dataset from Australia to present robust evidence on the causal impact of mental distress on cigarette smoking and alcohol drinking behaviours. We find that mental distress significantly increases the prevalence and intensity of either cigarette or alcohol consumption. Further analysis reveals that mental distress also substantially increases household monetary expenditures on either tobacco or alcohol. The impact is greater for lower educated individuals or children of smokers, and is slightly higher for males. Our findings highlight the importance of mental health screening and treatment programs, especially among lower educated individuals or children of smokers, to assist in the prevention of addictive activities. [ABSTRACT FROM AUTHOR]

This paper studies the impact of macroeconomic factors on co-movement in the foreign exchange rate markets. Data of foreign exchange rates from 24 merging markets is used to this end along with a dynamic spatial Durbin model as to examine spatial dependencies among markets. Our empirical findings show no evidence that cultural ties exert a role in spreading macroeconomic shocks in the exchange rate of a country to the exchange rates of other countries. Moreover, we show that economic closeness through foreign direct investment (FDI) and international bilateral trade is the most prominent channel in spreading macroeconomic shocks and spatial effects in emerging markets through the foreign exchange rates. In addition, geographical proximity reinforces the interdependence relationship of emerging markets. Our findings show that the co-movement of foreign exchange rate markets across the selected emerging markets is positively influenced by their gross domestic product (GDP) and interest rate differential and negatively affected by the terms of trade and remittance. In addition, we reveal that terms of trade, the inflation differential, and remittance are the most prominent fundamental factors affecting foreign exchange rate movements. [ABSTRACT FROM AUTHOR]

This paper studies the effect of the economic impact payment (EIP) on individual contributions to COVID-19 mitigation efforts in the USA, where the mitigation efforts are measured by the reduction of daily human mobility. I empirically estimate the effect of the EIP in April 2020 and use cellphone GPS data of 45 million smartphone devices as a proxy for human mobility across 216,069 Census Block Groups. The results show that when receiving the EIP, households significantly increased "Median Home Dwell Time" by an average of 3–5% (about 26–45 min). The paper highlights this unintended effect of the EIP, namely, that in addition to providing economic assistance, the EIP also helped increase individual contributions to mitigation efforts that slowed COVID-19 virus transmission in early 2020. [ABSTRACT FROM AUTHOR]

This paper uses time series of job search queries from Google Trends to predict the unemployment in Spain. Within this framework, we study the effect of the so-called digital divide, by age and gender, from the predictions obtained with the Google Trends tool. Regarding males, our results evidence a digital divide effect in favor of the youngest unemployed. Conversely, the forecasts obtained for female and total unemployment clearly reject such effect. More interestingly, Google Trends queries turn out to be much better predictors for female than male unemployment, being this result robust to age groups. Additionally, the number of good predictors identified from the job search queries is also higher for women, suggesting that they are more likely to expand their job search through different queries. [ABSTRACT FROM AUTHOR]

This paper derives the seasonal factors from the US temperature, gasoline price, and fresh food price data sets using the Kalman state smoother and the principal component analysis. Seasonality in this paper is modeled by the autoregressive process and added to the random component of the time series. The derived seasonal factors show a common feature: their volatilities have increased over the last four decades. Climate change is undoubtedly reflected in the temperature data. The three data sets' similar patterns from the 1990s suggest that climate change may have affected the prices' volatility behavior. [ABSTRACT FROM AUTHOR]

This paper extends the Baltagi et al. (J Econom 202:108–123, 2018; Advances in econometrics, essays in honor of M. Hashem Pesaran, Emerald Publishing, Bingley, 2021) static and dynamic ε -contamination papers to dynamic space–time models. We investigate the robustness of Bayesian panel data models to possible misspecification of the prior distribution. The proposed robust Bayesian approach departs from the standard Bayesian framework in two ways. First, we consider the ε -contamination class of prior distributions for the model parameters as well as for the individual effects. Second, both the base elicited priors and the ε -contamination priors use Zellner (Bayesian inference and decision techniques: essays in honor of Bruno de Finetti. Studies in Bayesian econometrics, vol 6, North-Holland, Amsterdam, pp 389–399, 1986)'s g-priors for the variance–covariance matrices. We propose a general "toolbox" for a wide range of specifications which includes the dynamic space–time panel model with random effects, with cross-correlated effects à la Chamberlain, for the Hausman–Taylor world and for dynamic panel data models with homogeneous/heterogeneous slopes and cross-sectional dependence. Using an extensive Monte Carlo simulation study, we compare the finite sample properties of our proposed estimator to those of standard classical estimators. We illustrate our robust Bayesian estimator using the same data as in Keane and Neal (Quant Econ 11:1391–1429, 2020). We obtain short-run as well as long-run effects of climate change on corn producers in the USA. [ABSTRACT FROM AUTHOR]

In this paper, score-driven time series models are used, in order to provide robust estimates of the seasonal components of Russian rouble (RUB) currency exchange rates for the period of 1999 to 2020. This paper is the first empirical application of score-driven models to the RUB to US dollar (USD) and RUB to Euro (EUR) currency exchange rates in the literature. The model includes score-driven local level, seasonality, and volatility components for a variety of probability distributions: Student's t distribution, skewed generalized t (Skew-Gen-t) distribution, exponential generalized beta distribution of the second kind (EGB2), normal-inverse Gaussian (NIG) distribution, and Meixner (MXN) distribution. The use of the MXN distribution is new in the literature of score-driven seasonality models. We show that the score-driven models of this paper are robust to changes in the currency exchange rate regimes of the Bank of Russia. We find that the annual seasonality of the RUB is significant, and it is in the range of ± 4 % . We review the determinants of the RUB seasonality using data on exports, imports, and primary income from the current account of the Russian Federation. The statistical performances of all score-driven models are superior to the statistical performance of the classical multiplicative seasonal autoregressive integrated moving average (ARIMA) model. Our results may motivate the practical use of score-driven models of the RUB exchange rate seasonality for financing, investment, or policy decisions. [ABSTRACT FROM AUTHOR]