Bayesian Inference of Multivariate Regression Models with Endogenous Markov Regime-Switching Parameters*

2020 ◽  
Author(s):  
Young Min Kim ◽  
Kyu Ho Kang
Keyword(s):  
Regime Switching ◽  
Multivariate Regression ◽  
Model Comparison ◽  
Marginal Likelihood ◽  
Empirical Studies ◽  
Regime Shifts ◽  
Parameter Estimates ◽  
Markov Regime Switching ◽  
Joint Dynamics ◽  
The Business Cycle

Abstract This study introduces a multivariate regression model with endogenous Markov regime-switching parameters, in which the regression disturbances and regime switches are allowed to be instantaneously correlated. For the estimation and model comparison, we develop a posterior sampling algorithm for the parameters, regimes, and marginal likelihood calculation. We demonstrate the reliability of the proposed method using simulation and empirical studies. The simulation study shows that neglecting the endogeneity leads to inaccurate parameter estimates, and that our marginal likelihood comparison chooses a correctly specified model. In the business cycle application, we find that the joint dynamics of the U.S. industrial production index (IPI) growth and unemployment rates are subject to three-state endogenous regime shifts. Another application to stock and bond return data suggests that negative shocks to the stock return seem to cause regime shifts from a low volatility state to a high volatility state of the financial markets. (JEL: C11, C53, E43, G12)

scholarly journals Modeling the exchange rate pass-through in Turkey with uncertainty and geopolitical risk: a Markov regime-switching approach

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Faik Bilgili ◽  
Fatma Ünlü ◽  
Pelin Gençoğlu ◽  
Sevda Kuşkaya
Keyword(s):  
Exchange Rate ◽  
Regime Switching ◽  
Regime Shifts ◽  
Demand Side ◽  
Economic Uncertainty ◽  
Markov Regime Switching ◽  
Content Type ◽  
Domestic Prices ◽  
The Exchange Rate ◽  
Pass Through

Purpose This paper aims to investigate the pass-through (PT) effect in Turkey by using quarterly data for the period 1998: Q1-2019: Q2 to understand the dynamic potential effects of exchange rates on domestic prices. Design/methodology/approach The paper launches several nonlinear models in which the basic determinants of domestic prices in Turkey are determined through Markov regime-switching models (MSMs). Hence, this research follows the variables of the consumer price index (CPI), USD exchange rate, gross domestic product (GDP; demand side of the economy), industrial production index (production side of the economy), economic uncertainty and geopolitical risk index for Turkey. Findings This work explores that the exchange rate and demand side of the economy (GDP) follow a positive nonlinear relationship with CPI at both regimes. The production side of the economy (IP) affects negatively the CPI during regime 0. Economic uncertainty influences the CPI positively at Regime 1, while geopolitical risk has a negative association with CPI at Regime 0. Eventually, the paper provides some policy proposals associated with the impacts of GDP, IP, economic uncertainty and geopolitical risk on CPI in Turkey. Originality/value One may claim that any PT model, which does not observe the possible structural or regime shifts in estimated parameters, might fail to estimate the coefficients unbiasedly and efficiently. Hence, this work differs from available relevant works in the literature since this paper considers linearity or nonlinearity important and reveals that the relevant PT model follows a nonlinear path rather than a linear path, this nonlinear path is converged strongly by MSMs and estimates the significant regime shifts in the constant term and, in parameters of independent variables of PT by MSMs.

Business Cycles and Apprenticeships

2021 ◽  
Author(s):  
Samuel Muehlemann ◽  
Stefan Wolter
Keyword(s):  
Labor Market ◽  
Business Cycle ◽  
Empirical Studies ◽  
Cost Effective ◽  
Skilled Labor ◽  
Market Failures ◽  
Task Forces ◽  
Apprenticeship Training ◽  
The Business Cycle ◽  
Over Time

The economic reasons why firms engage in apprenticeship training are twofold. First, apprenticeship training is a potentially cost-effective strategy for filling a firm’s future vacancies, particularly if skilled labor on the external labor market is scarce. Second, apprentices can be cost-effective substitutes for other types of labor in the current production process. As current and expected business and labor market conditions determine a firm’s expected work volume and thus its future demand for skilled labor, they are potentially important drivers of a firm’s training decisions. Empirical studies have found that the business cycle affects apprenticeship markets. However, while the economic magnitude of these effects is moderate on average, there is substantial heterogeneity across countries, even among those that at first sight seem very similar in terms of their apprenticeship systems. Moreover, identification of business cycle effects is a difficult task. First, statistics on apprenticeship markets are often less developed than labor market statistics, making empirical analyses of demand and supply impossible in many cases. In particular, data about unfilled apprenticeship vacancies and unsuccessful applicants are paramount for assessing potential market failures and analyzing the extent to which business cycle fluctuations may amplify imbalances in apprenticeship markets. Second, the intensity of business cycle effects on apprenticeship markets is not completely exogenous, as governments typically undertake a variety of measures, which differ across countries and may change over time, to reduce the adverse effects of economic downturns on apprenticeship markets. During the economic crisis related to the COVID-19 global pandemic, many countries took unprecedented actions to support their economies in general and reacted swiftly to introduce measures such as the provision of financial subsidies for training firms or the establishment of apprenticeship task forces. As statistics on apprenticeship markets improve over time, such heterogeneity in policy measures should be exploited to improve our understanding of the business cycle and its relationship with apprenticeships.

A Markov regime switching approach for hedging energy commodities

2008 ◽  
Vol 32 (9) ◽  
pp. 1970-1983 ◽  
Author(s):  
Amir H. Alizadeh ◽  
Nikos K. Nomikos ◽  
Panos K. Pouliasis
Keyword(s):  
Regime Switching ◽  
Markov Regime Switching

scholarly journals Protection and the Business Cycle

2003 ◽  
Vol 3 (1) ◽  
Author(s):  
Kyle Bagwell ◽  
Robert W. Staiger
Keyword(s):  
Business Cycle ◽  
Empirical Studies ◽  
Trade Policies ◽  
Trade Volume ◽  
Upward Trend ◽  
Theoretical Support ◽  
Empirical Regularities ◽  
The Business Cycle ◽  
Liberal Trade ◽  
The Relationship

Abstract Empirical studies have repeatedly documented the countercyclical nature of trade barriers. In this paper, we propose a simple theoretical framework that is consistent with this and other empirical regularities in the relationship between protection and the business cycle. Focusing on self-enforcing trade agreements, we find theoretical support for countercyclical movements in protection levels. The fast growth in trade volume that is associated with a boom phase facilitates the maintenance of more liberal trade policies than can be sustained during a recession phase in which growth is slow. We also find that acyclic increases in the level of trade volume give rise to protection, implying that whether rising imports are met with greater liberalization or increased protection depends on whether they are part of a cyclic upward trend in trade volume or an acyclic increase in import levels.

scholarly journals Inequality over the business cycle: the role of distributive shocks

2021 ◽  
pp. 1-30
Author(s):  
Marius Clemens ◽  
Ulrich Eydam ◽  
Maik Heinemann
Keyword(s):  
Income Inequality ◽  
Income Distribution ◽  
Business Cycle ◽  
Parameter Estimates ◽  
Panel Estimation ◽  
Bayesian Techniques ◽  
Elasticity Of Intertemporal Substitution ◽  
Ex Ante ◽  
The Business Cycle

Abstract This paper examines how wealth and income inequality dynamics are related to fluctuations in the functional income distribution over the business cycle. In a panel estimation for OECD countries between 1970 and 2016, although inequality is, on average countercyclical and significantly associated with the capital share, one-third of the countries display a pro- or noncyclical relationship. To analyze the observed pattern, we incorporate distributive shocks into an RBC model, where agents are ex ante heterogeneous with respect to wealth and ability. We find that whether wealth and income inequality behave countercyclically or not depends on the elasticity of intertemporal substitution and the persistence of shocks. We match the model to quarterly US data using Bayesian techniques. The parameter estimates point toward a non-monotonic relationship between productivity and inequality fluctuations. On impact, inequality increases in response to TFP shocks but subsequently declines. Furthermore, TFP shocks explain 17% of inequality fluctuations.

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