Empirica最新文献

This study aims to construct a sound theory of consumption convergence and empirically test its viability. To do this, we employ a Solovian framework in which the Keynesian exogenous savings-consumption allocation rule plays a crucial role. We demonstrate that consumption convergence performance is determined by both the average propensity to save (the indirect effect) and the average propensity to consume (the direct effect). In the empirical section, we use a system GMM estimator to test our consumption convergence equation on a panel data set of 177 countries and four income groups from 1970 to 2019. Our empirical findings indicate (i) absolute consumption convergence within high- and low-income country groups; (ii) strong evidence of conditional consumption convergence within high-, upper-middle-, and lower-middle-income groups; (iii) a robust and significant effect of the average propensity to save on the convergence process in high-, upper-middle-, and lower-middle-income groups; and (iv) a more robust and significant effect of the average propensity to consume in upper-middle- and lower-middle-income countries. In summary, we find that as income rises, the indirect impact plays a larger role in explaining consumption convergence, whereas the direct effect plays a smaller role. The policy implication of this conclusion is that policy makers in upper-middle- and lower-middle-income countries should restore the balance in the tradeoff between current and future consumption in favor of savings, as the former will harm consumption convergence within each middle-income group.

Export performance is a highly debated topic in the literature, with no consensus on how to measure it or what factors determine it. Most studies divide these factors into internal and external determinants, with a focus on internal determinants. This study, however, focuses on external determinants, namely agglomeration economies such as localization and urbanization economies and export spillovers, and their impact on a firm’s export intensity. Based on a large sample of Portuguese manufacturing SMEs over the period 2010 to 2018 (191,920 firm/year observations), the estimation results through the two-stage least squares method with fixed effects strongly indicate the existence of a positive relationship between agglomeration economies, particularly localization economies and export spillovers, and export performance. These findings suggest that firms located in areas with a high concentration of other firms in the same industry and other exporting firms tend to have better export performance, which has important implications for policymakers.

Three small Baltic economies of Estonia, Latvia and Lithuania have undergone extreme economical system change from the planned economy to the market one. The institutional infrastructure have been reorganized and all three countries joined the EU and Euro area. We aim to answer which channels of economic integration are of the largest importance for the small open European economies. We showed that all three countries could be treated as one region due to development, institutional and economic similarities. Secondly, we explore whether the trade or common currency is the main channel for the business cycle synchronization across the region of three small Baltic economies. The business cycle synchronization and trade intensity (TI) between the Baltic States and their main trading partners before and after joining the EU have been investigated as an example of an ex-post case for the small economies. We have observed a large increase in TI with the trading partners from EMU and EU countries, irrespective of the TI calculation method. The analysis of business cycle synchronization of the Baltic States with their main trading partners is captured by the correlations of the cyclical component of GDP series, using the quarterly real and de-trended GDP growth data from 1995 Q1 to 2019 Q4. The panel model has indicated an important empirical feature that the common currency strongly and significantly impacted the business cycle synchronization whilst the bilateral trade intensity between the Baltic States and their main trading partners have a significant negative effect on the business cycle synchronization when controlling for time effects. The Granger causality test confirmed that the most robust impulses to the Baltic States are coming from EU trading partners.

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.