Yongcheol Shin

• Professor (Full) at University of York

A large literature on modelling cross-section dependence in panels has been developed through interactive effects. However, there are areas where research has not really caught on yet. One such area is the one concerned with whether the regressors are correlated with factor loadings or not. This is an important issue because if the regressors are u...

A large literature on modelling cross-section dependence in panels has been developed through interactive effects. However, there are areas where research has not really caught on yet. One such area is the one concerned with whether the regressors are correlated with factor loadings or not. This is an important issue because if the regressors are u...

We review the literature on the Autoregressive Distributed Lag (ARDL) model, from its origins in the analysis of autocorrelated trend stationary processes to its subsequent applications in the analysis of cointegrated non-stationary time series. We then survey several recent extensions of the ARDL model, including asymmetric and nonlinear generalis...

We analyse the spatial attendance spillover applying spatial panel-data models with the Italian Football League data from 2001/2002 to 2016/2017. Our Quasi-Maximum Likelihood empirical results suggest that no significant spatial interaction was evident in earlier seasons (2001–2013), but modest spatial spillover was in play from 2013 to 2016. In ad...

We develop a new technique to estimate vector autoregressions with a common factor error structure by quantile regression. We apply our technique to study credit risk spillovers among a group of 17 sovereigns and their respective financial sectors between January 2006 and December 2017. We show that idiosyncratic credit risk shocks propagate much m...

We study the nonlinear limits to arbitrage in a model. When mispricing is small, arbitrage activity increases with mispricing because of the higher cost‐adjusted return. However, at high levels of mispricing, arbitrageurs are deterred by larger mispricing as funding constraints become more binding. Testing the model predictions on the index spot‐fu...

We propose a dynamic network quantile regression model to investigate the quantile connectedness using a predetermined network information. We extend the existing network quantile autoregression model of Zhu et al. (2019b) by explicitly allowing the contemporaneous network effects and controlling for the common factors across quantiles. To cope wit...

We propose a dynamic network quantile regression model to investigate the quantile connectedness using a predetermined network information. We extend the existing network quantile autoregression model of Zhu et al. (2019b) by explicitly allowing the contemporaneous network effects and controlling for the common factors across quantiles. To cope wit...

We develop a novel approach based on the canonical correlation analysis to identify the number of the global factors in the multilevel factor model. We propose the two consistent selection criteria, the canonical correlations difference (CCD) and the modified canonical correlations (MCC). Via Monte Carlo simulations, we show that CCD and MCC select...

We develop a unifying econometric framework for the analysis of heterogeneous panel data models that can account for both spatial dependence and common factors. To tackle the challenging issues of endogeneity due to the spatial lagged term and the correlation between the regressors and factors, we propose the CCEX-IV estimation procedure that appro...

We develop a technique to exploit forecast error variance decompositions to evaluate the macroeconomic connectedness embedded in any multi-country macroeconomic model with an approximate vector autoregressive (VAR) representation. We apply our technique to a large global VAR model covering 25 countries and derive vivid representations of macroecono...

Following recent contributions on migration flows, we contribute to the literature by relaxing restrictions on how multilateral resistance to migration (MRM) may affect province-pair-specific migration flows. We follow recent advancements in the three-dimensional (3D) panel data models with a hierarchical multifactor structure and develop the more...

Given the growing availability of large datasets and following recent research trends on multi-dimensional modelling, we develop three dimensional (3D) panel data models with hierarchical error components that allow for strong cross-section dependence through unobserved heterogeneous global and local factors. We propose consistent estimation proced...

We develop a novel approach based on the canonical correlation analysis to identify the number of the global factors in the multilevel factor model. We propose the two consistent selection criteria, the canonical correlations difference (CCD) and the modified canonical correlations (MCC). Via Monte Carlo simulations, we show that CCD and MCC select...

Motivated by the stylized fact that intraday returns can provide additional information on the tail behaviour of daily returns, we propose a functional autoregressive value-at-risk approach which can directly incorporate such informational advantage into the daily value-at-risk forecast. Our approach leads to greater flexibility in modelling the dy...

Given the growing availability of large datasets and following recent research trends on multi-dimensional modelling, we develop three dimensional (3D) panel data models with hierarchical error components that allow for strong cross-sectional dependence through unobserved heterogeneous global and local factors. We propose consistent estimation proc...

We develop the extended unit root testing procedure for dynamic panels characterised by slowly moving trends (SMT) and cross-section dependence (CSD). We allow SMT to follow the smooth logistic transition function and the components error terms to contain the unobserved common factors. We propose the two panel unit root test statistics, one derived...

This article empirically explores the effects of oil price on the Korean economy using a Global VAR model. First, we evaluate the average connectedness of oil price with the Korean domestic variables over the pre-crisis period. We then investigate the time-varying contribution of oil price to the Korean financial and real sectors during and after t...

Given the growing availability of big datasets which contain information on multiple dimensions and following the recent research trend on multidimensional modelling, we develop three-dimensional panel data models with threeway error components that allow for strong cross-sectional dependence (CSD) through unobserved heterogeneous global factors, a...

Korea is a textbook example of a small open economy which is susceptible to conditions overseas but cannot affect them itself. Policymakers in Korea would therefore naturally benefit from an enriched understanding of the connections that exist between the Korean and global economies. We provide a detailed summary of these linkages using the general...

We argue that arbitrageurs will strategically limit their initial investment in an arbitrage opportunity in anticipation of further mispricing caused by the deepening of noise traders' misperceptions. Such ‘noise momentum’ is an important determinant of the overall arbitrage process. We design an empirical strategy to capture noise momentum in a tw...

We use a network model to study the comovement of idiosyncratic sovereign credit risk in Europe. By estimating over rolling samples, we document evidence of excess comovement during the global nancial crisis and the European debt crisis that is indicative of contagion. We show that the intensity of bilateral spillovers is related to the portfolio i...

This paper addresses an important issue of modelling nonlinear asymmetric dynamics and unobserved individual heterogeneity in the threshold panel data framework, simultaneously. As a general approach, we develop the first-differenced GMM estimator, which allows both threshold variable and regressors to be endogenous. When the threshold variable bec...

Recently, an investigation of unobserved and time-varying multilateral resistance and omitted trade determinants has assumed a prominent role in order to precisely measure the Euro effects on trade. We implement two methodologies: the factor-based gravity model by Serlenga and Shin (The Euro Effect on Intra-EU Trade: Evidence from the Cross Section...

Xiao (2009) develops a novel estimation technique for quantile cointegrated time series by extending Phillips and Hansen’s (1990) semiparametric approach and Saikkonen’s (1991) parametrically augmented approach. This paper extends Pesaran and Shin’s (1998) autoregressive distributed-lag approach into quantile regression by jointly analysing short-r...

This paper proposes a unified framework for accommodating both time and cross-sectional dependence in modelling technical efficiency in stochastic frontier models by combining the exogenously driven factor-based approach and an endogenous threshold efficiency regime selection mechanism. This approach is able to deal with both weak and strong cross-...

We develop a technique to evaluate macroeconomic connectedness in any multi-country macroeconomic model with an approximate VAR representation. We apply our technique to a large Global VAR covering 25 countries and derive vivid representations of the connectedness of the system. We show that the US, the Eurozone and the crude oil market exert a dom...

We examine which methods are appropriate for estimating dynamic panel data models in empirical corporate finance. Our simulations show that the instrumental variable and GMM estimators are unreliable, and sensitive to the presence of unobserved heterogeneity, residual serial correlation, and changes in control parameters. The bias-corrected fixed-e...

This paper proposes an e¢ cient test designed to have power against alternatives where the cointegrating regression error follows stationary MS regime switching dy- namics. We model an equilibrium process where its error correction adjustments are dierent in dierent regimes characterized by the hidden state Markov chain process. Using a general non...

We employ dynamic threshold partial adjustment models to study the asymmetries in firms' adjustments toward their target leverage. Using a sample of US firms over the period 2002--2012, we document a negative impact of the Global Financial Crisis on the speed of leverage adjustment. In our subperiod analysis, we find moderate evidence of cross-sect...

This paper proposes a nonlinear panel data model which can endogenously generate both ‘weak’ and ‘strong’ cross-sectional dependence. The model’s distinguishing characteristic is that a given agent’s behaviour is influenced by an aggregation of the views or actions of those around them. The model allows for considerable flexibility in terms of the...

We argue that arbitrageurs will strategically limit their initial investment in an arbitrage opportunity in anticipation of further mispricing caused by the deepening of noise traders’ misperceptions. Such ‘noise momentum’ is an important determinant of the overall arbitrage process. We design an empirical strategy to capture noise momentum in a tw...

We develop a global vector autoregressive model to study the transmission of information between currency spot markets. Our model accounts for both simultaneous and dynamic interactions between exchange rates and order flows using historical data from the Reuters Dealing 2000-1 platform for the period May-August 1996. By analysing the network topog...

Motivated by a stylized fact that intraday returns can provide additional information on the tail behavior of the daily returns, we propose a novel semiparametric functional autoregressive value-at-risk model (FARVaR), which can directly incorporate such informational advantage into the value-at-risk forecast. Our approach explicitly allows for tim...

Korea is a textbook example of a small open economy which is susceptible to conditions overseas but cannot affect them itself. Policymakers in Korea would therefore naturally benefit from an enriched understanding of the connections that exist between the Korean and global economies. We provide a detailed summary of these linkages using the general...

This paper investigates the adjustment of the prices of four key petroleum products in the UK following changes in the price of crude oil. We find significant evidence that the pre-tax prices of diesel, kerosene, and gas oil adjust more rapidly in an upward than a downward direction, but that the pre-tax price of unleaded petrol adjusts symmetrical...

We investigate the asymmetric relationships between aggregate inflation and the second and third moments of the cross-sectional distribution of relative prices using a modified Calvo pricing model with regime-dependent price rigidities. Calibration experiments reveal that the inflation-standard deviation and inflation-skewness relationships exhibit...

Established monetary theory typically assumes that the pass-through from policy-controlled interest rates to longer term rates and yields is complete, rapid and symmetric. We investigate these assumptions by applying the Nonlinear ARDL (NARDL) model advanced by Shin, Yu and Greenwood-Nimmo (2013) to the analysis of interest rate pass-through in the...

This paper develops a cointegrating nonlinear autoregressive distributed lag (NARDL) model in which short- and long-run nonlinearities are introduced via positive and negative partial sum decompositions of the explanatory variables. We demonstrate that the model is estimable by OLS and that reliable long-run inference can be achieved by bounds-test...

This paper investigates the adjustment of the prices of four key petroleum products in the UK following changes in the price of crude oil. We find significant evidence that the pre-tax prices of diesel, kerosene, and gas oil adjust more rapidly in an upward than a downward direction, but that the pre-tax price of unleaded petrol adjusts symmetrical...

This study advances previous work on the effects of trade and technological change on labour markets within the framework of Heckscher–Ohlin trade theory. We provide evidence for an unskilled labour abundant developing country by employing dynamic heterogeneous panel estimation techniques. For South African manufacturing, trade‐mandated increases i...

This paper analyses the international linkages of the Korean economy using the GVAR model developed by Greenwood-Nimmo, Nguyen and Shin (2012a, J. Appl. Econometrics). By employing a combination of generalized impulse response analysis and forecast error variance decompositions, we uncover a number of interesting phenomena. Among our most important...

In an earlier paper the authors proposed a two‐step approach to examine dynamic transmission mechanism under which globalization factors foster technology efficiency. In this paper the MSS model is extended by combining a panel threshold regression technique. This threshold stochastic frontier panel data model enables the analysis of regime‐specifi...

Extending Shleifer and Vishny (1997), we show that arbitrageurs will strategically limit their initial investment in an arbitrage opportunity in anticipation of further mispricing caused by the deepening of noise traders’ misperceptions. Such ‘noise momentum’ is an important determinant of the overall arbitrage process. We develop a state-dependent...

This chapter demonstrates the usefulness of the GVAR modelling framework as a tool for scenario-based forecasting and counterfactual analysis. Working with the GVAR model developed by Greenwood-Nimmo, Nguyen and Shin (2010, J. Appl. Econometrics), we first show how probabilistic forecasting can be applied to the analysis of global imbalances. Proba...

We develop a dynamic panel threshold model of capital structure to test the dynamic trade-off theory, allowing for asymmetries in firms’ adjustments toward target leverage. Our novel estimation approach is able to consistently estimate heterogeneous speeds of adjustment in different regimes as well as to properly test for the threshold effect. We c...

We employ a two-step approach in investigating the dynamic transmission channels under which globalization factors foster technical efficiency by combining a dynamic efficiency analysis in the stochastic frontier framework, and a time series approach based on VAR and spectral analysis. Using the dataset of the 18 EU countries over 1970-2004, we fin...

We derive a new method of modelling the Taylor Rule in a system setting which expressly accounts for its combination of I(0) and I(1) series. Using a long sample of US data, our model provides modest support for an inertial Taylor-type rule. However, estimation across rolling windows indicates that the inflation and output preferences of the Fed ha...

This paper analyses the international linkages of the Korean economy using the GVAR model developed by Greenwood-Nimmo, Nguyen and Shin (2012a, J. Appl. Econometrics). By employing a combination of generalised impulse response analysis and forecast error variance decompositions, we uncover a number of interesting phenomena. Among our most important...

Interest in the interface of nonstationarity and nonlinearity has been increasing in the econometric literature. This paper provides a formal method of testing for nonstationary long memory against the alternative of a particular form of nonlinear ergodic processes; namely, exponential smooth transition autoregressive processes. In this regard, the...

We generalize the portfolio shifts model advanced by Evans and Lyons (2002a; b), and develop the dynamic asymmetric portfolio shifts (DAPS) model by explicitly allowing for possible market under- and overreactions and for asymmetric pricing impacts of order flows. Using the Reuters D2000-1 daily trading data for eight currency markets over a four-m...

This paper utilizes the semi-parametric functional autoregressive approach to model the time-varying distribution of UK monthly inflation rates using sectoral inflation rates. Our approach is free of any assumptions on the structure of the distributions, or the number of dimensions in which the distributions may vary. Our framework provides an alte...

Recently, Shin (2007) proposes new estimation procedure to analyse asymmetric thresh- old eects in a threshold autoregressive model in dynamic panels with unobserved individ- ual eects when the number of time periods is …xed by combining time series techniques on nonlinear threshold modelling with the existing FD-GMM estimation techniques. This pap...

Comparing investments opportunities in the emerging and the developed markets is an important issue in the international portfolio management. However, it is well-established that the stock market returns are non-normal and have time-varying distributions. This creates a challenge in ranking alternative investment strategies especially in a dynamic...

We apply a global vector autoregressive (GVAR) model to the analysis of inflation, output growth and global imbalances among a group of 33 countries (26 regions). We account for structural instability by use of country-specific intercept shifts, the timings of which are identified taking into account both statistical evidence and our knowledge of h...

Existing studies have used the dynamic, partial adjustment model of leverage to test the trade-off theory against alternative theories. The challenge of this approach is to consistently estimate both the speed of leverage adjustment and the long-run relationship underlying target leverage in short panels with individual fixed effects. This paper co...

This paper extends the portfolio shifts model advanced by Evans and Lyons (2002a,b) by allowing for persistent mispricing and asymmetric pricing impacts of order flow. In particular, market under- and overreactions could happen and persist due to the presence of `behaviourally biased' traders while the asymmetric pricing impacts stem from varied ri...

This paper proposes a new panel model of cross-sectional dependence. The model has a number of potential structural interpretations that relate to economic phenomena such as herding in financial markets. On an econometric level it provides a flexible approach to the modelling of interactions across panel units and can generate endogenous cross-sect...

We extend GLS detrending procedure to testing for unit roots against STAR and SETAR alternatives. Monte Carlo simulations and applications to DM/Yen real exchange rates demonstrate that GLS detrending-based nonlinear unit root tests are more powerful than OLS detrending-based counterparts.

Empirically, the sum of GARCH parameter estimates is found to be close to unity, suggesting that the conditional volatility of most stock return data are likely to follow an integrated GARCH (IGARCH) process. However, such an extremely high persistence in unconditional variance may be overstated because of neglected structural breaks or parameter c...

We follow recent developments of panel data studies and allow for the existence of both observed and unobserved common factors where their individual responses are allowed to be heterogeneous. We then develop a generalized Hausman-Taylor estimation methodology, and apply our proposed estimation technique to an analysis of the gravity equation of bi...

This book provides a comprehensive description of the state-of-the-art in modelling global and national economies. It introduces the long-run structural approach to modelling that can be readily adopted for use in understanding how economies work, and in generating forecasts for decision- and policy-makers. The book contains a thorough description...

This book provides a comprehensive description of the state-of-the-art in macroeconometric modelling and describes the ‘long-run structural modelling approach’ applied to the modelling of national economies in a global context. The first part of the book discusses the ways in which economic theory and econometric analysis can be brought together to...

This book provides a comprehensive description of the state-of-the-art in macroeconometric modelling and describes the ‘long-run structural modelling approach’ applied to the modelling of national economies in a global context. The first part of the book discusses the ways in which economic theory and econometric analysis can be brought together to...

This book provides a comprehensive description of the state-of-the-art in macroeconometric modelling and describes the ‘long-run structural modelling approach’ applied to the modelling of national economies in a global context. The first part of the book discusses the ways in which economic theory and econometric analysis can be brought together to...

This book provides a comprehensive description of the state-of-the-art in macroeconometric modelling and describes the ‘long-run structural modelling approach’ applied to the modelling of national economies in a global context. The first part of the book discusses the ways in which economic theory and econometric analysis can be brought together to...

This book provides a comprehensive description of the state-of-the-art in macroeconometric modelling and describes the ‘long-run structural modelling approach’ applied to the modelling of national economies in a global context. The first part of the book discusses the ways in which economic theory and econometric analysis can be brought together to...

This book provides a comprehensive description of the state-of-the-art in macroeconometric modelling and describes the ‘long-run structural modelling approach’ applied to the modelling of national economies in a global context. The first part of the book discusses the ways in which economic theory and econometric analysis can be brought together to...

This book provides a comprehensive description of the state-of-the-art in macroeconometric modelling and describes the ‘long-run structural modelling approach’ applied to the modelling of national economies in a global context. The first part of the book discusses the ways in which economic theory and econometric analysis can be brought together to...

This book provides a comprehensive description of the state-of-the-art in macroeconometric modelling and describes the ‘long-run structural modelling approach’ applied to the modelling of national economies in a global context. The first part of the book discusses the ways in which economic theory and econometric analysis can be brought together to...

This book provides a comprehensive description of the state-of-the-art in macroeconometric modelling and describes the ‘long-run structural modelling approach’ applied to the modelling of national economies in a global context. The first part of the book discusses the ways in which economic theory and econometric analysis can be brought together to...

This book provides a comprehensive description of the state-of-the-art in macroeconometric modelling and describes the ‘long-run structural modelling approach’ applied to the modelling of national economies in a global context. The first part of the book discusses the ways in which economic theory and econometric analysis can be brought together to...

This paper proposes a new testing procedure to detect the presence of a cointegrating relationship that follows a globally stationary smooth transition process. In the context of nonlinear smooth transition error correction models (ECMs) we provide two simple operational versions of the tests. First, we obtain the associated nonlinear ECM-based tes...

This paper proposes a panel-based mean group test for the null of stationarity against the alternative of unit roots in the presence of both heterogeneity across cross-section units and serial correlation across time periods. Using both sequential and joint asymptotic analyses the proposed test statistic is shown to be distributed as standard norma...

This paper proposes a simple testing procedure to distinguish a unit root process from a globally stationary three-regime self-exciting threshold autoregressive process. Following the threshold cointegration literature we assume that the process follows the random walk in the corridor regime, and therefore we propose that the null of a unit root be...

It is now quite common to have panels in which both T, the number of time series observations, and N, the number of groups, are quite large and of the same order of magnitude. The usual practice is either to estimate N separate regressions and calculate the coefficient means, which we call the Mean Group (MG) estimator, or to pool the data and assu...

In this paper we follow recent developments of panel data studies and explicitly allow for the existence of unobserved common time-specific factors where their individual responses are also allowed to be heterogeneous across cross section units. In the context of this extended panel data framework we generalize the Hausman-Taylor estimation methodo...

This paper proposes the panel-based mean group tests for the null of stationarity against the alternative of unit roots in the presence of both heterogeneity across crosssection units and serial correlation across time periods. Using both sequential and joint asymptotic analyses the proposed test statistic is shown to be distributed as standard nor...