Empirical Economics最新文献

This study investigates the impact of significant wildfires from 2019 to 2022 on nine sectors within the US capital markets, utilizing a dataset encompassing 161 wildfires. Employing a combination of parametric and nonparametric tests, alongside regression analysis, the research scrutinizes how capital markets in distinct sectors respond to wildfire events, revealing nuanced effects. In sectors directly impacted, the insurance industry displays sensitivity to fire costs, with explicit country or event mentions correlating with sustained returns. Conversely, the real estate sector experiences diminished returns during prolonged wildfires, while the forestry and timber industry exhibits heightened sensitivity to fire costs, especially when ignited by lightning. Within indirect impact sectors, the health industry shows vulnerability to fire-related fatalities, with subsequent negative correlations with country mentions. In the food industry, fire costs contribute positively to returns, while duration and size yield negative effects. The transportation industry witnesses a gradual decline in returns, escalating with the number of fire days or associated costs. In resilience and mitigation sectors, utilities demonstrate recovery post-wildfires, contrasting with consistent declines in the energy sector. Among interconnected sectors, the travel and tourism industry sees increased returns tied to the number of victims, with events caused by human actions having a more pronounced impact. This research underscores the significance of tailored risk assessment and mitigation strategies, offering valuable insights for investors and policymakers navigating the intricate relationship between environmental events and financial markets.

Abstract

While the product and labour market imperfections reveal efficiency losses, they may influence technology adoption and its change, raising the endogeneity issue of productivity and efficiency estimates. Using a two-step approach, this work offers the endogeneity-corrected stochastic frontier for such a contemporaneous relation and accounts for efficiency and productivity losses due to market imperfections. A modified frontier function, defined as the residue per capital unit, has been drawn from the Cobb–Douglas function to estimate the terms containing the product and labour market imperfections along with other factors capturing the levels of technology, scale and technical efficiency. First, a standard frontier panel model estimates technology and technical efficiency terms with a proxy function in polynomials of market imperfection terms used for the contemporaneous relation, and then a GMM approach applies to the residue to estimate the parameters containing market imperfections. The estimated results using the three-digit industries across 17 major Indian states for 2008–2016 reveal a strong presence of product and labour market imperfections and associated efficiency losses. The efficiency in the product market has been lower and has further deteriorated in most industries, but not in the labour market.

Abstract

We employ an extended Stochastic Impacts by Regression on Population, Affluence and Technology (STIRPAT) model combined with the environmental Kuznets curve and machine learning algorithms, including ridge and lasso regression, to investigate the impact of institutions on carbon emissions in a sample of 22 European Union countries over 2002 to 2020. Splitting the sample into two: those with weak and strong institutions, we find that the results differ between the two groups. Our results suggest that changes in institutional quality have a limited impact on carbon emissions. Government effectiveness leads to an increase in emissions in the European Union countries with stronger institutions, whereas voice and accountability lead to a fall in emissions. In the group with weaker institutions, political stability and the control of corruption reduce carbon emissions. Our findings indicate that variables such as population density, urbanization and energy consumption are more important determinants of carbon emissions in the European Union compared to institutional governance. The results suggest the need for coordinated and consistent policies that are aligned with climate targets for the European Union as a whole.

We study the effects of expected initial wages, expected wage growth, and observed and unobserved heterogeneity in the choice of college major in a sample of American college graduates. We propose a three-stage empirical model that relates future earnings to individual choices. In the first stage, starting from revealed choices, observed wages, and life-cycle wage profiles, we estimate the expectation on initial wages and wage growth from the individual point of view, where the panel structure of the data allows us to produce estimates corrected for self-selection bias. We find substantial differences in expected real wages and expected real wage growth between majors and that both characteristics of life cycle earnings influence major choice. Our parametric models show a strong correlation between salary trends and major choice, whereas semiparametric models yield less reliable results. We interpret our results as being consistent with agents being rational and as a validation for our estimation strategy based on counterfactual imputation.

The paper discusses the results of a selection of a set of monthly indicators to be used as predictors of the quarterly index of Italian service turnover. A mixed frequency approach based on sparse temporal disaggregation is used, which outperforms the classical methods of the Chow and Lin family, allowing both a high number of regressors by the LASSO method and stable estimates. The application refers to the turnover in transport, a sector strongly affected in 2020 by the dramatic movements due to the COVID-19 pandemic and the resurgence of inflation at the end of 2021. The monthly indicators are selected from 143 time series: 56 series of business surveys in transport about both the climate and frequency of the answers; 18 series from Assaeroporti about both passengers and cargo flights split by national and international routes; 69 series of monthly turnover in industry split by both sector of economic activity and reference market. The sample spans the months from January 2010 to December 2021 for both seasonally adjusted and unadjusted data. Several aspects of the estimation are considered: the stability of selected indicators over the quarters 2017–2021; their forecasting performance; the reliability of the estimates in terms of their monthly pattern.

This study examines the heterogeneity in job mobility and earnings growth among workers who were mismatched in their previous jobs due to different reasons. Mismatched is defined as working in jobs that are not related to the highest degree field. Using a panel dataset derived from the National Survey of College Graduates, I find that workers who were previously mismatched due to the unavailability of jobs in related fields (demand-mismatched) are more likely to make complex moves, i.e., changing both employer and job title, and experience higher earnings growth relative to their matched counterparts. The earnings growth among previously matched workers and workers who were mismatched due to other reasons, such as a change in career interests (supply-mismatched), is generally not significantly different. However, supply-mismatched workers encounter negative earnings growth after making simple moves, i.e., changing only employer. Further, heterogeneous earnings growth patterns are found among mismatched workers in different stages of career and between female and male mismatched workers.

This research investigates the spillovers of global liquidity to Asia–Pacific countries, focusing on the contradictory effects of policy-driven liquidity created by monetary stances in advanced economies and market-driven liquidity generated by the private banking sector. Our findings stand in sharp contrast to previous studies, showing that shifts in macro-financial indicators in Asia–Pacific economies are predominantly influenced by market-driven shocks rather than those of policy-driven liquidity. Specifically, liquidity shocks associated with surges in cross-border credit flows, especially those denominated in US dollars, drive up asset prices and have boosting effects on inflation and economic output. A positive shock to market liquidity also results in an appreciation pressure on domestic currencies and a short-term rise in interest rates. However, excess liquidity shocks caused by the Bank of Japan’s adjustments in shadow short rates and balance sheets have a negative effect on inflation and bring about temporary depreciation pressure on Asian currencies. Surprisingly, we find that Asian responses to financial easing associated with the Fed’s monetary policy change are not well-pronounced.

Abstract

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

Accurate real-time macroeconomic data are essential for policy-making and economic nowcasting. The rising interest in analyses at the sub-national level cannot be served as such data are currently not available. In this paper, I introduce a real-time database for German regional economic accounts. The database contains real-time information for nine macroeconomic aggregates and the 16 German states. I conduct both a revision analysis and a nowcasting experiment for real gross domestic product. By pooling the states together, the first official estimates show no systematic revision errors. The pooling, however, suppresses the revision characteristics of single states. For half of the 16 German states I find that the first estimates are no optimal predictions, thus, leaving room for improvements in the future. The real-time nowcasts for real gross domestic product growth based on a mixed-frequency vector autoregression are very accurate and beat several benchmark models. More regional data would help to better inform the model, thereby increasing its nowcast performance even further.