Empirical Economics

Jalles, João Tovar; Kiendrebeogo, Youssouf; Lam, Raphael; Piazza, Roberto

doi: 10.1007/s00181-024-02586-zpmid: N/A

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.

Tsang, Andrew

doi: 10.1007/s00181-024-02575-2pmid: N/A

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.

Adil, Masudul Hasan; Chaubal, Aditi

doi: 10.1007/s00181-024-02584-1pmid: N/A

One of the most widely researched macroeconomic relationships is money demand stability, which helps monetary authorities understand what motivates economic agents hold real money balances and whether it can predict inflation. However, endogenous structural shocks to macroeconomic fundamentals have often been criticized for distorting the equilibrium relationship among economic variables. These shocks usually stem from socioeconomic and political changes, behavior of economic agents, and random shocks. We examine the presence of cointegrating relationships between money demand and scale and opportunity cost variables while allowing for multiple endogenous structural breaks in the cointegrating vectors in the Indian context for the period 1996:Q2–2021:Q2. We utilize the Narayan and Popp (J Appl Stat 37(9):1425–1438, 2010) test to identify the break dates in each series and then employ the Maki (Econ Model 29(5):2011–2015, 2012) cointegration approach to establish the presence of long-run relationships between money demand and its covariates. Our study finds the presence of stable long-run relationships in the money demand function, implying that monetary authorities may target narrow and broad monetary aggregates as an indicator or treat them as an information variable to anchor the inflation expectations of economic agents under the current flexible inflation-targeting framework.

Fei, Yijie

doi: 10.1007/s00181-024-02572-5pmid: N/A

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.

Cooray, Arusha; Özmen, Ibrahim

doi: 10.1007/s00181-024-02579-ypmid: N/A

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.

Kauko, Karlo

doi: 10.1007/s00181-024-02576-1pmid: N/A

The Newcomb-Benford law states that the frequency of different leading significant digits in many datasets typically follows a specific distribution. Deviations from this law are often a sign of data manipulation. There has been no established method to test whether the non-reliability of observations depends on some potential explanatory variables. A novel method to address this issue is presented. If a leading significant digit has a higher observed frequency than implied by Benford’s distribution, such observations are particularly likely to be non-reliable. Dividing the frequency in Benford’s distribution by the observed frequency of the same leading significant digit yields an ordinal explained variable. The method is applied to bank deposit data collected in interviews. Many interviewees have provided rounded data, which may be a problem. Answers seem unreliable if the respondent belongs to the age group 51–65, has only primary education, does not live alone, and lives in a city.

Papathanasiou, Spyros; Kenourgios, Dimitris; Koutsokostas, Drosos; Pergeris, Georgios

doi: 10.1007/s00181-024-02583-2pmid: N/A

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.

Le, Chau; Nguyen, Huyen; Vo, Duc

doi: 10.1007/s00181-024-02573-4pmid: N/A

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.

Tavor, Tchai

doi: 10.1007/s00181-024-02574-3pmid: N/A

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.

Maiti, Dibyendu; Neogi, Chiranjib

doi: 10.1007/s00181-024-02577-0pmid: N/A

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.