Empirica最新文献

A stochastic volatility estimation of VIX index’s latent volatility is used for the United States of America, as a proxy for the adjustments in the levels of investors’ uncertainty related to current and future economic policies. The impact of monetary policy stance on such measure is examined in the framework of the distributed lag non-linear models (DLNM). We place this analysis in the literature stream emphasizing the various sources of heterogeneity concerning investors’ expectations. The main finding is that the monetary policy does impact non-linearly the adjustments in investors’ predictions. While a tighter monetary policy does generally contribute to an increase in VIX’s latent volatility, the shape of such effect varies across different GLM and GAM specifications of DLNM. This outcome remains robust, even if: (1) we control for the global price of Brent crude and consumers’ confidence; (2) we use, instead of the stochastic framework, a Markov-switching GARCH-based estimator; or (3) we replace the monetary policy instrument with monetary policy uncertainty. We argue that accounting for its nonlinear effects on financial markets is of critical importance for the design of a monetary policy pursuing global financial stability.

This paper examines the impact of Artificial Intelligence (AI) on early retirement (ER) decisions in Europe. For the analysis, we utilize microdata from the Survey of Health, Ageing and Retirement in Europe, along with occupation-level data on AI advances and AI exposure. Initially, we investigate the influence of AI advances and AI exposure separately, finding in both instances a significant reduction in ER likelihood, though this only applies to workers with higher education. Subsequently, we explore the interaction between AI advances and AI exposure concerning ER probability. This interaction proves critical in determining AI’s impact on ER transitions. Specifically, we observe a significant reduction in ER probabilities for workers whose occupations exhibit high levels of AI advances and high expectations for further implementation of this technology in the future. Finally, we jointly analyse the interaction between AI advances, AI exposure, and education level. This analysis highlights that workers’ ER probabilities may either increase or decrease in response to the AI revolution, depending on their education level and the characteristics of their occupations in terms of AI advances and AI exposure.

Many countries in Europe have experienced a steady increase in housing prices over the past decade, which continued even during the recent crisis. We analyze a panel of 15 European countries over the period 2000–2020. We find that demand-side determinants, such as GDP, unemployment, wage and population, strongly influence housing prices. Nevertheless, we suggest that construction costs, access to finance (credit to GDP), and financing costs (long-term interest rate) should be included to avoid biased results. We find that financial development can significantly affect housing prices in the long run. We confirm the robustness of our results by conducting a lag sensitivity analysis of selected determinants. In addition, we find a negative effect of the GFC and a positive effect of the Covid crisis on housing prices. Furthermore, we find that countries with a mild reaction to or a quick recovery from the GFC experienced significantly higher housing price growth.

The onset of the COVID-19 pandemic in the United States may have led investors or other individuals to expect sharp drops in output and rising prices, as well as drastic changes in fiscal and/or monetary to deal with the crisis. This paper analyses the co-movement between expected inflation and interest in the U.S. by using a battery of wavelet tools over the period from January 21, 2020 to March 28, 2022. Wavelet methods are used to examine the linkages between expected inflation and nominal interest rates of varying terms, focusing on the direction of co-movement and their sub-time horizons. Both bivariate wavelet and partial wavelet models that incorporate daily COVID-19 case counts or a financial stress variable find that the relationship holds primarily in the longer short-run (more than 6 months), with connections stronger for maturities of 5 years than for 1 year or less. The expectation related to the ‘inflation–interest rate’ nexus and type of bond maturity seem to be significantly shaped by the pandemic peak and anticipated duration of the disease. More precisely, the longer the anticipated duration of the pandemic is, the higher the expected inflation rate, bond yield rate, and maturity are. The interaction between expected inflation and interest seems to be very sensitive to pandemic and financial stress in terms of lead-lag status, in the very short to short-run, for 5 and 10 years bond maturity. This seems to be explained by investor hazard to a new particular unknown stimulus caused by the pandemic and its socio-economic consequences.

Three decades before the Great Recession (the 2008 financial and economic crisis) were marked by the continuous growth of current account imbalances and income inequality. This period of high globalization is accompanied by financial liberalization and an increase in trade openness. The empirical investigations of the causes of global imbalances show that growing income inequalities are worsening the current account. After the fall of the Berlin Wall, new EU member states experienced an increase in trade openness accompanied by current account deficits and financial liberalization, but also an increase in income inequality. The Great Recession led to a decrease in imports in these countries and an improvement in the current account. The goal of our research is primarily to examine the relationship between income inequality, current account, and economic openness in the new EU member states. We show that rising income inequality linked with financial liberalization is connected with the deterioration of the current account in new EU member states. Financial liberalization relates to an increase in household domestic debt, contributing to a deterioration of the current account.

The availability heuristic is a cognitive bias that affects various aspects of decision-making, including financial decisions. Based on a randomized controlled experiment, this study assesses the effectiveness of a debiasing treatment designed to prevent the effect of the availability heuristic in student loan decision-making. Experimental subjects were explained that there is a bias that may affect the decision of whether or not to pursue a master’s degree and take out a graduate loan to finance it, and they were recommended to base their decision on reliable and verified sources of information as well as expert advice. This specific debiasing strategy is tested empirically. Specifically, this study shows positive causal effects of the debiasing intervention on two indices of student loan decision-making, which were constructed as summary indicators of student loan debt attitude, the perception that significant referents approve the student loan indebtedness, financial self-efficacy in student loan decision-making, and graduate loan borrowing intention. The article highlights the need for higher education institutions seeking to make financial education effective to be concerned with reporting on (and raising awareness of) psychological factors that are present in making financial decisions as well.

Using a comprehensive dataset of firm-level administrative value added tax (VAT) filings, this study investigates the behavioral responses of small firms to tax incentives. In South Korea, the standard VAT rate has remained at 10% since the introduction of the VAT system in 1977. However, small firms with a total annual revenue below 48 million KRW (approximately $46,000) benefit from a reduced VAT rate under the simplified VAT regime. This study uncovers an excess mass of firms in the revenue distribution precisely at the 48 million KRW threshold. Importantly, this response pattern varies depending on factors such as business sectors, the geographic location of firms and the year of their establishment. The disparities in tax liabilities at the threshold are identified as one of the potential factors driving these results.

Abstract

Trust plays a vital role in shaping numerous socio-economic behaviors. However, little is known about how significant life events, such as adverse and beneficial health events, shape up trust. Therefore, we examine the impact of positive and negative health events on general trust using the LISS panel (3911 respondents) from the Netherlands. The primary health event variable is constructed by comparing self-reported health in 2017 with 2018, while trust measured in 2019 (after the health survey) is used as the outcome variable. We find a significant and negative impact of adverse health events on trust, while positive health events have an insignificant effect. We perform several robustness checks that support our main findings. Further investigation shows that negative health events impact trust by reducing psychological wellbeing and social interactions. The results provide fresh insights into the health events and trust nexus.

This paper analyses the impact of highways on the distribution of economic activities between urban agglomerations and peripheral regions in the European Union. In doing so, I use an empirical strategy based on the land use theory employing disaggregated economic and infrastructure data. To address endogeneity, I apply an IV strategy exploiting non-local highway construction as a source of exogenous variation. I find that highways contribute to the diffusion of urban economic activities into surrounding areas, reducing the income gap between European agglomerations and peripheries. Reduced-form estimations suggest that the gap would have been nearly 3% higher in 2020 if the highway networks of European countries had remained at the level of 1990. The study concludes that transportation infrastructure policies can alleviate regional income disparities, increasing economic convergence between urbanised and less urbanised areas.

This study focuses on the examination of the side effects of the European cohesion policy (ECP), in particular, the direct and indirect effects of the European structural and investment (ESI) funds on business cycle co-movement in the Euro area (EA) countries. The results of analysis performed using the simultaneous equations framework in the 2000–2019 period reveal that increasing ESI payments within the cohesion policy have overall contributed to more synchronized EA business cycles. Even though the ESI payments do not seem to directly support synchronization, probably because of their procyclical nature, we find that the unintended benefits of the ESI payments with respect to the synchronization lie in their indirect positive effects, which outweigh the negative direct effect. The total positive effect of the ECP emerges because increasing investment from the ESI funds promotes the EA business cycle synchronization via trade, bilateral FDI, and income similarity. Meanwhile, similar evidence has not been confirmed for the specialization channel.