The impact of corporate governance on employment relations in South Korea: the shareholder versus stakeholder perspectives

This study empirically examined the impact of corporate governance on employment relations outcomes utilizing a comprehensive data set drawn from 214 Korean firms. The study contrasted the stakeholder and shareholder perspectives of corporate governance in investigating the impact of corporate governance on employment relations outcomes. The results showed that the stakeholder corporate governance orientation (as compared to the shareholder orientation) had positive relationships with education/training expense, average employee tenure and industrial relations (IR) climate, as well as a negative association with number of strikes. Overall, the results implied that the stakeholder orientation of firms led to more beneficial effects for employees and more consensual relations with labour unions than the shareholder orientation did.     

Efficient predictability of stock return volatility: The role of stock market implied volatility

This study examines the predictability of stock market implied volatility on stock volatility in five developed economies (the US, Japan, Germany, France, and the UK) using monthly volatility data for the period 2000 to 2017. We utilize a simple linear autoregressive model to capture predictive relationships between stock market implied volatility and stock volatility. Our in-sample results show there exists very significant Granger causality from stock market implied volatility to stock volatility. The out-of-sample results also indicate that stock market implied volatility is significantly more powerful for stock volatility than the oil price volatility in five developed economies.     

The impact of corporate governance on employment relations in South Korea: the shareholder versus stakeholder perspectives

This study empirically examined the impact of corporate governance on employment relations outcomes utilizing a comprehensive data set drawn from 214 Korean firms. The study contrasted the stakeholder and shareholder perspectives of corporate governance in investigating the impact of corporate governance on employment relations outcomes. The results showed that the stakeholder corporate governance orientation (as compared to the shareholder orientation) had positive relationships with education/training expense, the level of average employee tenure and industrial relations climate, and had a negative association with number of strikes. Overall, the results implied that the stakeholder orientation of firms led to more beneficial effects for employees and more consensual relations with labor unions than the shareholder orientation did.     

Ex post tests for short-and long-run optimization

The purpose of this paper is to develop tests of long-run equilibrium models where the long-run is defined as the state where the observed levels of output and capital are consistent with optimizing behavior. We use the implied relationship between a restricted translog cost function and derived demand equations to provide a series of nested tests which can be interpreted as ex post tests for short- and long-run optimization behavior. A set of parameter restrictions on the translog system are specified for testing whether observable levels of capital and/or output of a firm correspond to the long-run optimal level. Our tests of the validity of long-run equilibrium specifications are based on data for 28 German industries for the period 1960-1981. For most of the industries the set of restrictions implied by long-run equilibrium had to be rejected.     

Does Evidence on Regional Economic Convergence Depend on the Estimation Strategy? Outcomes from Analysis of a Set of NUTS2 EU Regions

Abstract

The regional economic convergence/divergence issue has been discussed extensively recently, but results obtained are not always interpretable unequivocally as a consequence of the different estimation strategies used. As it is widely recognized, the most common theoretical framework applied to measure the speed of economic convergence among countries or regions remains the β-convergence approach, linked to the neoclassical Solow model. There have been many attempts to consider variations of the basic cross-sectional specification ranging from panel data models to Bayesian spatial econometric techniques. The application of spatial econometric methodologies is an essential tool for proper statistical inference on regional data. In this context, the aim of this paper is to connect the different results obtained in the literature. More specifically, we address whether or not evidence on convergence depends upon the estimation strategy, by taking the same set of data and systematically comparing the results obtained from different estimation strategies. The results from a set of NUTS2 EU regions conclude that both the model implied by the cross-sectional analysis and the one referring to the space-time dynamics incorporated in the panel specification point to convergence. The concept of convergence implied is, however, quite different, as demonstrated throughout the paper.     

Equilibrium Unemployment Dynamics in a Panel of OECD Countries

We focus on the equilibrium unemployment rate as a parameter implied by a dynamic aggregate model of wage and price setting. The equilibrium unemployment rate depends on institutional labour market institutions through mark‐up coefficients. Compared with existing studies, the resulting final equation for unemployment has a richer dynamic structure. The empirical investigation is conducted in a panel data framework and uses OECD data up to 2012. We propose to extend the standard estimation method with time dummies to control and capture the effects of common and national shocks by using impulse indicator saturation (WG‐IIS), which has not been previously used on panel data. WG‐IIS robustifies the estimators of the regression coefficients in the dynamic model, and it affects the estimated equilibrium unemployment rates. We find that wage co‐ordination stands out as the most important institutional variable in our data set, but there is also evidence pointing to the tax wedge and the degree of compensation in the unemployment insurance system as drivers of equilibrium unemployment.     

Using qualitative approach to forecasting regime switches

Drastic changes (named regime switches) often exist in economic and financial time series causing the forecasting of time series difficult. Hence, we need robust models to detect and forecast the regime switches. Most previous studies apply quantitative methods to forecast time series and regime switches. Contrast to these studies, this study attempts a novel approach to use a qualitative method to forecast regime switches. Fuzzy set/qualitative comparative analysis (fsQCA), based on fuzzy set and logic theory, yields the relationships between antecedent combinations and outcome. Studies support fsQCA analysis is more proper to reflect the real situations. Hence, this study uses fsQCA to analyze the autoregressive relationships of the upward and downward regime switches in the in-sample data. Then, the relationships are used to forecast the regime switches in the out-of-sample data. Taiwan Capitalization Weighted Stock Index is taken as the data for analysis. The empirical results show that fsQCA provides strong predictive validities.     

Highway congestion and congestion tolls

Highway congestion is ubiquitous. We model the speed-flow relationship, identifying private and social costs, and the implied congestion toll for a number of proposed formulations. Using data for a limited access highway, we estimate these speed-flow relationships and find that flow as a quadratic function of speed fits best. The unit of observation is the individual vehicle and flow is measured in terms of the vehicles which passed a point shortly before or after the reference vehicle. Maximum possible flow occurs at 30–35 mph and the congestion toll is infinite for slower speeds. Rush-hour drivers have greater speeds for a given volume of traffic and thus congestion tolls must vary by time of day.     

Bayesian Inference in Spatial Sample Selection Models

In this study, we consider Bayesian methods for the estimation of a sample selection model with spatially correlated disturbance terms. We design a set of Markov chain Monte Carlo algorithms based on the method of data augmentation. The natural parameterization for the covariance structure of our model involves an unidentified parameter that complicates posterior analysis. The unidentified parameter – the variance of the disturbance term in the selection equation – is handled in different ways in these algorithms to achieve identification for other parameters. The Bayesian estimator based on these algorithms can account for the selection bias and the full covariance structure implied by the spatial correlation. We illustrate the implementation of these algorithms through a simulation study and an empirical application.     

On the informational efficiency of S&P500 implied volatility

Implied volatility is often considered to represent a market's prediction of future volatility. If such a market was to generate efficient volatility forecasts, implied volatility should reflect all relevant conditioning information. The purpose of this paper is to determine whether a publicly available and commonly used implied volatility index, the VIX index (as published by the Chicago Board of Options Exchange) is in fact efficient with respect to a wide set of conditioning information. Results indicate that the VIX index is not efficient with respect to all elements in the information set that may be used to form volatility forecasts.     

Decomposing Federal Funds Rate forecast uncertainty using time-varying Taylor rules and real-time data

This paper studies uncertainty about out-of-sample interest rate forecasts implied by an estimated Taylor rule. It is shown that the Taylor rule leads to a decomposition of forecast uncertainty into an element that depends on uncertainty about the future state of the economy and another element that is related to uncertainty about the monetary policy reaction function of the Federal Reserve. Uncertainty about one-quarter ahead Federal Funds Rate forecasts from 1975 to 2007 is estimated and analyzed using a real-time data set for the U.S.     

The role of implied volatility in forecasting future realized volatility and jumps in foreign exchange,stock, and bond markets

We study the forecasting of future realized volatility in the foreign exchange, stock, and bond markets from variables in our information set, including implied volatility backed out from option prices. Realized volatility is separated into its continuous and jump components, and the heterogeneous autoregressive (HAR) model is applied with implied volatility as an additional forecasting variable. A vector HAR (VecHAR) model for the resulting simultaneous system is introduced, controlling for possible endogeneity issues. We find that implied volatility contains incremental information about future volatility in all three markets, relative to past continuous and jump components, and it is an unbiased forecast in the foreign exchange and stock markets. Out-of-sample forecasting experiments confirm that implied volatility is important in forecasting future realized volatility components in all three markets. Perhaps surprisingly, the jump component is, to some extent, predictable, and options appear calibrated to incorporate information about future jumps in all three markets.     

Offshoring versus backshoring: Empirically derived bundles of relocation drivers,and their relationship with benefits

This paper describes an empirically derived classification of the various factors that influence offshoring and backshoring decisions based on data from 275 offshoring and 160 backshoring projects. The study developed one set of factor bundles for offshoring and another set of such bundles for backshoring; these sets were then compared, and their relationships with post-relocation benefits were analyzed. These benefits were also grouped into bundles based on the empirical relationships. This research contributes an empirically derived classification scheme of decision factors for both offshoring and backshoring as well as an analysis of the relationships between decision factors and benefits for each type of relocation direction.     

Cointegration in a macroeconomic system

This paper investigates the long-run relationships within a set of six quarterly time-series on the Austrian economy by means of cointegration. After analysing the univariate properties, especially with respect to the appropriate seasonal filter, the maximum-likelihood method proposed by Johansen (1988) is applied to estimate and test the cointegrating relationships. We found three such relations, implying that the system is driven by three independent stochastic time trends. In a next stage we investigate whether the empirically determined cointegrating relationships are compatible with implications derived from the neoclassical growth model with exogenous stochastic technical progress. It is found that the Austrian data strongly reject the propositions that the real interest rate and the log ratios of consumption to output, investment to output, and the real gross wage sum to output are stationary.     

Google data in bridge equation models for German GDP

Interest in the use of “big data” when it comes to forecasting macroeconomic time series such as private consumption or unemployment has increased; however, applications to the forecasting of GDP remain rather rare. This paper incorporates Google search data into a bridge equation model, a version of which usually belongs to the suite of forecasting models at central banks. We show how such big data information can be integrated, with an emphasis on the appeal of the underlying model in this respect. As the decision as to which Google search terms should be added to which equation is crucial —- both for the forecasting performance itself and for the economic consistency of the implied relationships —- we compare different (ad-hoc, factor and shrinkage) approaches in terms of their pseudo real time out-of-sample forecast performances for GDP, various GDP components and monthly activity indicators. We find that sizeable gains can indeed be obtained by using Google search data, where the best-performing Google variable selection approach varies according to the target variable. Thus, assigning the selection methods flexibly to the targets leads to the most robust outcomes overall in all layers of the system.     

Explaining US–UK Interest Rate Differentials: A Reassessment of the Uncovered Interest Rate Parity in a Bayesian Framework*

In this paper, we test the uncovered interest rate parity (UIRP), allowing for transitory deviations from it. These deviations may arise from variations in risk premia, errors in expectations and linearization errors, and are modelled as a zero‐mean noise around the restrictions implied by the UIRP on a vector autoregression (VAR) in the interest rate differential and the spot exchange rate. Importantly, this approach includes the traditional one as a special case, which is derived by simply setting the noise to zero. When the noise is set to zero the UIRP is rejected, but if we allow for some degree of noise the UIRP is strongly supported by the data. Thus the UIRP relation does not hold exactly, but on average, with a stationary risk premium as opposed to a constant one. This result implies that analysing the effects of policy experiments under the null of the UIRP may be both safe and useful.     

Indifference,indecision, and coin-flipping

This article operationalizes a non-empty relation as implied if strict preference and indifference jointly do not completely order the choice set. Specifically, indecision is operationalized as a positive preference for delegating choice to a least predictable device.     

基于SCOR模型的供应链流程管理架构研究

从企业流程建模的理论出发,对SCOR模型加以扩展,提出了一个基于SCOR模型的供应链流程管理建模架构,描述了该架构的组成要素以及各要素间的联系,为供应链流程管理提供了模型支持。     

The number of banking relationships and the business cycle: New evidence from Colombia

We study the determinants of multiple bank–firm relationships using a uniquely rich data set comprised of information on individual loans of a large number of firms in Colombia. We control for firm-specific variables and find that the business cycle exerts important influence on the number of bank relationships sustained by firms. Our evidence suggests that the number of bank relationships is counter-cyclical, decreasing during macroeconomic expansions and increasing during contractions. However, this effect is stronger for large firms which have more access to alternative sources of funding.     

Does the option market produce superior forecasts of noise‐corrected volatility measures?

This paper assesses the robustness of the relative performance of spot‐ and options‐based volatility forecasts to the treatment of microstructure noise. Robustness of the results to the method of constructing option‐implied forecasts is also investigated. Using a test for superior predictive ability, model‐free implied volatility, which exploits information in the volatility ‘smile’, and at‐the‐money implied volatility, which does not, are both tested as benchmark forecasts of a range of alternative volatility proxies. The results provide compelling evidence against the model‐free forecast for three Dow Jones Industrial Average stocks, over a 2001–2006 evaluation period. In contrast, the at‐the‐money implied volatility forecast is given strong support for the three equities over this period. Neither benchmark is supported for the S&P500 index. Importantly, the main qualitative results are invariant to the method of noise correction used in measuring future volatility. Copyright © 2008 John Wiley & Sons, Ltd.