scholarly journals IDENTIFYING LATENT GROUPED PATTERNS IN COINTEGRATED PANELS

2019 ◽  
Vol 36 (3) ◽  
pp. 410-456 ◽  
Author(s):  
Wenxin Huang ◽  
Sainan Jin ◽  
Liangjun Su

We consider a panel cointegration model with latent group structures that allows for heterogeneous long-run relationships across groups. We extend Su, Shi, and Phillips (2016, Econometrica 84(6), 2215–2264) classifier-Lasso (C-Lasso) method to the nonstationary panels and allow for the presence of endogeneity in both the stationary and nonstationary regressors in the model. In addition, we allow the dimension of the stationary regressors to diverge with the sample size. We show that we can identify the individuals’ group membership and estimate the group-specific long-run cointegrated relationships simultaneously. We demonstrate the desirable property of uniform classification consistency and the oracle properties of both the C-Lasso estimators and their post-Lasso versions. The special case of dynamic penalized least squares is also studied. Simulations show superb finite sample performance in both classification and estimation. In an empirical application, we study the potential heterogeneous behavior in testing the validity of long-run purchasing power parity (PPP) hypothesis in the post–Bretton Woods period from 1975–2014 covering 99 countries. We identify two groups in the period 1975–1998 and three groups in the period 1999–2014. The results confirm that at least some countries favor the long-run PPP hypothesis in the post–Bretton Woods period.

2013 ◽  
Vol 58 (01) ◽  
pp. 1350007 ◽  
Author(s):  
A. F. M. KAMRUL HASSAN ◽  
RUHUL SALIM

Relative population growth affects relative prices through the so-called Balassa–Samuelson (BS) mechanism and that in turn impacts PPP. This paper empirically investigates the relationship between the PPP exchange rate and relative population growth in a panel of 80 selected countries. Following the BS hypothesis, this paper argues that relative population growth affects nominal wages that impact price levels and thereby impacts PPP. Using panel cointegration and fully modified ordinary least square (FMOLS), the empirical results show that there is a stable relationship between PPP exchange rate and relative population growth in the long run. These empirical findings suggest that population growth have an important role in exchange rate determination through PPP.


2004 ◽  
Vol 07 (01) ◽  
pp. 31-44
Author(s):  
FOTIOS SIOKIS ◽  
CHRIS CHRISTODOULOU

A common view among recent studies on purchasing power parity is that the post-Bretton Woods period is far too short to reveal any significant parity reversion in individual series of real exchange rates. The answer depends on the statistical techniques being used. This study uses alternative econometric time-series technique, which does not require long sample sizes, and reports strong evidence of mean reversion in dollar-based real exchange rates. Further analysis of the estimated impulse responses indicates that the persistence in real exchange rate changes is difficult to detect because the short and long run dynamics interact in such a way that the impulse response weights exhibit a rapid decay.


1992 ◽  
Vol 24 (12) ◽  
pp. 1301-1306 ◽  
Author(s):  
Dimitris A. Georgoutsos ◽  
Georgios P. Kouretas

2018 ◽  
Vol 24 (8) ◽  
pp. 1015-1028 ◽  
Author(s):  
Martin Falk ◽  
Xiang Lin

This article provides new evidence on the stability of the long-run income elasticity of tourism and travel demand by use of the recently developed smooth time-varying cointegration regression model. The estimations control for relative purchasing power parity of the source country and make use of a specific country dataset where domestic and foreign overnight stays are available over a longer period of time (Switzerland, 1934–2015). Results show that the income elasticity of foreign overnight stays peaks at approximately two in the early 1960s, drops to around one in the early 1980s and from then on remains stable until the end of the sample. Domestic income elasticity reaches its highest levels in the 1930s, then steadily falls towards one in the mid-1960s, and therefrom remains stable until 2015. Different phases in the tourism area life cycle might be a major explanatory factor for variation in income elasticities over time.


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