JournalTOCs

Empirical Economics
Journal Prestige (SJR): 0.532

Citation Impact (citeScore): 1
Number of Followers: 16

Hybrid journal (It can contain Open Access articles)
ISSN (Print) 1435-8921 - ISSN (Online) 0377-7332
Published by Springer-Verlag

[2469 journals]

Account-level analytic hierarchical mixing modeling for credit risk of
Chinese Government financing vehicle portfolios
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  Abstract: Traditional credit risk measurement models, requiring fair amounts of default debts, have trouble in measuring the true default probability of Government financing vehicle (GFVs) loans in China. In this study, an analytic hierarchical mixing model (AHMM) was proposed to estimate the real states of Chinese GFVs with little default observations. AHMM outputs abstract risk indices for each loan based on the account-level GFV data, mapped to the probability of default by a calibration curve for loan decision, dynamic risk control, and stress testing. Furthermore, we also applied municipal bond data from the U.S. to AHMM and found that the accuracy ratio was 0.89 for the U.S. data and 0.84 for the Chinese data. The fitting error range based on U.S. data is [− 0.07 0.117], which is significantly lower than the Chinese GFV data, [− 0.10 0.2115]. Thus, although AHMM could be a credit risk model with few default observations, it works better on data with more default observations. The methodology in this study can be used on aggregate data to evaluate the entire Chinese GFV portfolio and thus bring a clear sovereign solvency picture to regulators and investors.
  PubDate: 2022-06-01
One-step oracle procedure for semi-parametric spatial autoregressive model
and its empirical application to Boston housing price data
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  Abstract: Abstract Issues concerning spatial dependence among cross-sectional units in econometrics have received more and more attention. Motivated by a Boston housing price data analysis, this paper studies the sparse inference of varying coefficient partially linear spatial autoregressive model, which is quite valuable in econometrics with high-dimensional data. A novel, efficient and convenient one-step variable selection procedure is proposed by using a twofold penalty for simultaneous estimation and variable selection of the parametric components and varying coefficient functions, in which the varying coefficient functions are approximated by the B-spline basis. Under some regularity conditions, asymptotic properties of the resulting estimators are established, including consistency, asymptotic normality and the oracle property. Besides, the optimal choices of the tuning parameters are discussed and a practical iterative algorithm based on the locally quadratic approximation approach is presented for implementation. Finally, extensive numerical simulations and a Boston housing price data analysis are conducted to confirm the finite sample performance and theoretical findings of the new method.
  PubDate: 2022-06-01
A dynamic analysis of household debt using a self-organizing map
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  Abstract: Abstract The Korean consumer credit panel offers a well-organized set of microdata representing various characteristics of individual borrowers. To overcome the difficulty of fragmented microdata details, we construct a cluster of Korean consumers’ credit, to develop a self-organizing map that visualizes individuals’ characteristics along two dimensions. The result of cluster analysis reveals that most borrowers belong to one large cluster representing diligent borrowers who honor their loan payments. Conversely, several small clusters that represent borrowers with high default probability are identified, and we also found that these borrowers’ characteristics vary. No significant change is found in the structure of the cluster, even when the aggregate amount of consumer credit is increased. Moreover, the expansionary monetary policy did not change the quantitative structure of household debt in Korea.
  PubDate: 2022-06-01
Disaggregating the impact of oil prices on European industrial equity
indices: a spatial econometric analysis
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  Abstract: Abstract This study investigates the relationship between daily returns of oil and ten European industrial equity indices for the period 2008–2017 using the spatial econometric technique. In our settings, the historical co-movements of sectoral returns are incorporated while modelling the contemporaneous relationships between oil and European sectoral returns. After controlling for regional and global equity risk factors, we find that oil returns pose a significantly positive effect on sectoral indices’ returns in line with previous studies. However, the magnitude of economic impact found mostly by earlier studies was largely underestimated without considering the co-movements of sectoral indices. The use of spatial econometric technique allowed us to disaggregate the total impact into a direct (due to oil price) and an indirect (due to spillover effect because of intra-industry co-movements) effect of oil price changes. Our results indicate that the direct economic impact of changes in oil prices on industrial returns is almost 31% more than what has been found by earlier studies. The negative spatial dependence among sectoral indices provides a useful tool to identify the source of the indirect impact of oil on overall equity prices in Europe that in turn explains the overestimation of direct impact by 31%.
  PubDate: 2022-06-01
Strategic supermarket pricing of private labels and manufacturer brands
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  Abstract: Abstract Large, low-cost entrants can have a disrupting impact on incumbents. Supercenters may influence competing supermarkets’ prices, but their effects on competition between supermarkets’ private labels and manufacturer brands remain poorly understood. This study examines the impact of Wal-Mart Supercenters on supermarkets’ strategic use of private labels and the control they may exercise over the pricing of manufacturer brands. We use a structural model to investigate alternative pricing scenarios in which the supermarkets have varying control over manufacturer-brand retail prices. The analysis is applied to the milk market in the Dallas/Fort Worth metroplex in an early period of Supercenter growth: 1996–2001. We find that Wal-Mart induces supermarkets to price their private label more competitively and has a very small effect on the pricing of the manufacturer brand. We also identify the type of consumers Wal-Mart Supercenters can attract from supermarkets, leaving incumbents to face a different composition of consumers. Consumers that continue shopping at traditional supermarkets are found to be less price-sensitive, view incumbents as less heterogeneous, and experience the manufacturer brand as more differentiated from private labels.
  PubDate: 2022-06-01
A comprehensive impact evaluation of active labour market programmes in
Slovenia
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  Abstract: Abstract Using administrative database containing work history and programme participation for the entire national workforce, the paper evaluates Slovenia’s four main active labour market programmes: institutional training, on-the-job training, wage subsidies and public works. The studied outcomes range from post-unemployment employment probability and job quality to cumulative effects on employment and earnings over the longer run, and also include programmes’ cost-effectiveness. We identify programme effects by comparing outcomes of treatment and control groups using propensity score matching. The results show that the programmes perform rather well judged both by their impact on labour market outcomes and by their cost-effectiveness: except for public works, all programmes are found to have a net benefit in terms of government expenditures. Our results are robust to time-invariant unobserved heterogeneity in the treatment and control groups, as we corroborate the baseline propensity score matching results with a difference-in-difference estimator.
  PubDate: 2022-06-01
Do minimum wages improve self-rated health' Evidence from a natural
experiment
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  Abstract: Abstract We analyze whether the introduction of the general minimum wage in Germany in 2015 had an effect on workers’ self-rated health. To this end, we use survey data linked to administrative employment records and apply difference-in-differences regressions combined with propensity score matching. This approach enables us to control for a vast set of potential confounding variables. We find a health improving effect among the individuals who were most likely to be affected by the reform. Our results indicate that workers’ improved satisfaction with pay, their reduced working hours, and a reduction in time pressure at work may drive this result.
  PubDate: 2022-06-01
Fiscal reaction functions for the advanced economies revisited
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  Abstract: Abstract We revisit the relationship between the primary balances/GDP and debt/GDP ratios (fiscal reaction function, FRF), in the advanced economies, showing that using adequate tests and estimators leads to question the validity of the current consensus. Using data for 1961–2019, we find that long-run FRFs exist only in a small number of advanced economies (Belgium, Germany, Greece, Norway, Portugal and Sweden), with polynomial effects with fiscal fatigue only in Germany. These results warn against the widespread practice of estimating homogeneous polynomial panel FRFs. Limiting the sample to 1961–2007, thus excluding the 2008 crisis and its aftermath, FRFs hold also in Canada, Ireland, Italy (polynomial), Spain and USA, though not in Germany, and the coefficients are generally larger. Particularly, after 2008 European Union countries appear somehow to have been more likely to implement FRFs.
  PubDate: 2022-06-01
Estimating the effects of ESG scores on corporate credit ratings using
multivariate ordinal logit regression
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  Abstract: Abstract We estimated the effects of Environmental, Social, and Governance (ESG) scores on the credit ratings of firms in the sectors of manufacturing, mining and quarrying, wholesale and retail trade, information and communication, and real estate activities and located in North America, Europe, and Asia using a multivariate ordinal logit model. We use credit ratings by the S&P and Fitch agencies and the Refinitiv ESG pillar scores as measures of the performance of firms on sustainability matters. We found that the Environmental pillar score is the dimension of sustainability that most contributes to improving the goodness-of-fit of the credit rating model. It has a significant positive effect on credit ratings in all sectors investigated, with stronger effects for mining and quarrying firms. Firms that manage environmental matters better than their industry peers are perceived as more resilient to long-term risks and these tend to be rewarded by credit rating agencies. Some mixed evidence between credit rating agencies is found for the social and governance dimensions in terms of statistical significance and estimated marginal effects by sector.
  PubDate: 2022-06-01
Impact of the Indian “demonetization” policy on its export
performance
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  Abstract: Abstract We examine the export impact of the Indian government’s surprise move to invalidate 86% of existing currencies overnight. This ‘demonetization' was undertaken in an attempt to eliminate illegal and untaxed transactions, and to make the financial system more reliant on electronic transactions. This policy was implemented within a production structure that significantly depended on cash and informal credit sources, and a banking infrastructure that did not reach all corners of the economy. Due to the unexpectedness of this policy, the impact is predicted to have been stronger in the short run than the long run as the economy adjusted to the new system. The synthetic control method (SCM) achieves this, and with its ability to accommodate scenarios where the policy impact may vary across post-treatment periods, provides a suitable tool for our analysis. Additionally the unexpectedness of the policy circumvents anticipation issues making the scenario an ideal candidate for SCM analysis. No long-term improvements though significant short-term losses in exports values due to this policy are uncovered that are robust across alternate specifications and estimation methods.
  PubDate: 2022-06-01
Economic impact payment, human mobility and COVID-19 mitigation in the USA
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  Abstract: Abstract 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.
  PubDate: 2022-06-01
The role of externalities in fiscal efficiency
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  Abstract: Abstract Fiscal efficiency is determined not only by the municipality’s local characteristics but also by externalities from the neighborhood. In this paper, we study municipalities’ fiscal efficiency and assess the importance of such externalities in shaping local fiscal efficiency. The quantification of externalities is challenging because municipalities interact in complex ways. We build a municipality-specific indicator of externalities that considers the effect of the geographic and social neighborhoods. Externalities tend to increase when municipalities are close and have more significant differences in social development. To analyze the role of externalities in public spending efficiency, we propose a novel way to compare efficiency models by ensuring similarity in their structural properties (inputs, outputs, and orientation). In this situation, when one does not consider the network effect that a specific municipality receives, one could be misevaluating the municipality’s actual efficiency level. We apply our model to Brazilian municipalities and find that socio-economic externalities play an essential role in local public spending efficiency. Many municipalities are deemed efficient when they are not if we do not explicitly consider the effect of externalities on the municipality’s local performance. Our findings highlight the importance of socio-economic cooperation and integration among municipalities as a tool to achieve better fiscal performance.
  PubDate: 2022-06-01
Oral interventions in the foreign exchange market: evidence from Australia
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  Abstract: Abstract In response to the large fluctuations of the Australian dollar in the beginning of the twenty-first century, the Reserve Bank of Australia (RBA) started to express a preference for a weaker domestic currency through public speeches and monetary policy statements in order to achieve balanced economic growth. We construct a novel Exchange Rate Stance Index (ERSI) to measure the magnitude of RBA’s oral interventions in the foreign exchange market. We employ the ERSI in a structural vector autoregressive model to quantify the impact of RBA’s communication on the Australian dollar and overall economic activity. An unanticipated increase in the ERSI leads to a significant weakening of the Australian dollar and considerably stimulates output. The ERSI shocks account for a sizeable fraction of Australia’s macroeconomic fluctuations, comparable to the exchange rate shocks. The impact of ERSI on output is largely transmitted through the exchange rate depreciation.
  PubDate: 2022-06-01
Does economic inequality breed murder' An empirical investigation of
the relationship between economic inequality and homicide rates in
Canadian provinces and CMAs
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  Abstract: Abstract National and international research documents a relationship between greater economic inequality and higher homicide rates. However, much of this work uses simple cross sections at high levels of aggregation rather than longer time series of cities or districts and lacks controls for a more substantial range of confounding factors. Using longitudinal Canadian provincial-level data over the period 1982 to 2017, we occasionally find a positive correlation between inequality and homicides rates. However, the relationship between income inequality and homicide rates in Canada reverses to become negative when looking at Canadian census metropolitan areas (CMAs). Moreover, the province-level result between greater inequality and homicide rates also appears to break down once accounting for regional effects. We conclude that much of the literature that finds a relationship between greater economic inequality and homicide rates needs to be re-examined within a longer time and more disaggregated framework.
  PubDate: 2022-06-01
What do one hundred million transactions tell us about demand elasticity
of gasoline'
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  Abstract: Abstract The price elasticity of gasoline demand is a key parameter in evaluation of various policies. However, most of the literature uses aggregate data to identify this elasticity. Temporal and spatial aggregation make such elasticity estimates biased. We employ a unique dataset of all gasoline transactions in Iran during a 4-month period around an unexpected exogenous price change to identify that price elasticity. We also identify a significant withholding behavior by consumers in response to anticipated price changes. The consumers reduce or postpone their purchases when they expect a decrease in prices. Controlling for date fixed effects would eliminate homogeneous withholding responses. However, heterogeneous responses to this anticipated price change would lead to an overestimation of price elasticity. After controlling for date, individual, and location fixed effects as well as the withholding behavior, we estimate a robust significant price elasticity of − 0.085. Aggregation of the same data by week, month, and city yields an estimate of − 0.3, indicating a significant bias in earlier studies.
  PubDate: 2022-06-01
Aggregation, asymmetry, and common factors for Bangladesh’s exchange
rate–trade balance relation
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  Abstract: Abstract We present an application of the recent CS-ARDL methodology in the context of a country’s trade balance–exchange rate relationship. The trade balance is expected to deteriorate first before improving in response to currency depreciation and vice versa, widely known as the J-curve effect satisfying the Marshall–Lerner condition in the long run. Combining bilateral and aggregate analysis in one setting by constructing specific panel data with one reference country, we find that aggregate analysis is sensitive to our allowance for heterogeneity. Estimates using the aggregate time series data show evidence favoring the J-curve relation, whereas the aggregate analysis resulting from the panel time series data shows that currency appreciation improves trade balance in Bangladesh in the long run, which goes against the Marshall–Lerner condition. With the reference of the existing commodity-level literature, we argue that this atypical scenario lines with the realities of a ‘small’ economy like Bangladesh, where her exporters attempt to maintain their market share with some government support. The study provides essential policy suggestions by identifying the significant contributors to Bangladesh’s trade balance–exchange rate relationship: China, Japan, and Singapore.
  PubDate: 2022-06-01
Exploring the technology–healthcare expenditure nexus: a panel error
correction approach
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  Abstract: Abstract Technology is perceived as a key factor driving the increase in per capita healthcare expenditure. We assess this effect between 1981 and 2019 for a panel of OECD member countries using a panel error correction model, which was estimated using the dynamic common correlated effect approach of Chudik and Pesaran (J Econom 188(2):393–420, 2015). 10.1016/j.jeconom.2015.03.007. Results corroborate previous findings that medical technology and healthcare expenditure follow a long-run relationship. Incorporating heterogeneity and controlling for cross-sectional dependence and endogeneity reveals substantial variation in medical technology’s effect across OECD member countries. Overall, medical technology is a key factor in driving the increase in per capita healthcare expenditure for less than half of the panel of OECD member countries. This finding is consistent across three different technology proxies and suggests that policymakers should utilize country-specific coefficients to inform decisions.
  PubDate: 2022-06-01
The effect of neighbourhood and spatial crime rates on mental wellbeing
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  Abstract: Abstract This paper attempts to provide new evidence on the indirect cost of neighbourhood crime rates on mental wellbeing of residents. Crime places a heavy burden on the economy, and it receives significant attention from the public. Yet, the connection between crime and health for victims and non-victims is not well captured in the literature. Using spatial methodology, we differentiate the effect on mental wellbeing of residents due to the crime rates in their immediate neighbourhood (local) and crime rates in the surrounding areas (spatial). The main innovation of the paper is to use these crime rates at small geographical level (around 8500 residents) to better translate the changes in crime in the neighbourhoods and their effects on a person’s mental wellbeing. This is different to other studies that looked at crime incidences in larger geographical units. Our estimation results show that the increase in local and spatial crime rates against the property negatively affect the mental wellbeing of residents. The negative impact of spatial crime rates against the person is also present and is 6.7 times larger than the effect of property crime rates.
  PubDate: 2022-05-24
Liquidity and realized covariance forecasting: a hybrid method with model
uncertainty
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  Abstract: Abstract This paper investigates the realized covariance forecasting and liquidity effects on the covariance. The realized covariance is calculated based on the high frequency data of CSI 300 stock index and futures, and nonlinear support vector regression (SVR) approach is employed to evaluate the out-of-sample forecasting ability of HAR-type models. Then, we propose the hybrid method, named the weighted average windows (WAveW) method based on both OLS and SVR forecasts, to accommodate model uncertainty. The empirical results find that the performance of the WAveW method based on SVR forecasts obtains more accurate forecasting than the OLS and SVR methods, and the incorporation of liquidity helps to improve the forecasting ability. From the portfolio selection perspective, we show that our new method achieves higher economic value, which further confirms the effectiveness of our proposed hybrid method. The results are robust under alternative rolling windows, liquidity, covariance and cojumps.
  PubDate: 2022-05-21
Price bubbles of agricultural commodities: evidence from China’s
futures market
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  Abstract: Abstract 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.
  PubDate: 2022-05-20