Wy are the transition paths in China and Eastern Europe different?

The purpose of this paper is to provide a framework linking communist regime collapse and privatizing economic reforms. The framework permits us to explain why certain communist regimes lost their monopoly of political power while others have not. We show that the essential difference between those communist regimes which survived economic reform and those which did not, lies in the nature of the privatization reform introduced by the communist leadership. The privatization that we call ‘Market‐Leninist’, was implemented in China and Vietnam while the second type of privatization, termed ‘Embezzlement for a rainy day’ was the type of privatization implemented in Eastern Europe. We show, in the context of a game between rulers and the population, that the size of the repressive apparatus is the key element determining the type of privatization chosen by the rulers. JEL classification: P2, P3.     

Political budget cycles in new versus established democracies

Like other recent studies, we find a political deficit cycle in a large cross-section of countries, but show that this result is driven by the experience of “new democracies”. The political budget cycle in new democracies accounts for the finding of a budget cycle in larger samples that include these countries and disappears when they are removed from the larger sample. The political deficit cycle in new democracies accounts for findings in both developed and less developed economies, for the stronger cycle in weaker democracies, and for differences in the political cycle across governmental and electoral systems. Our findings may reconcile two contradictory views of pre-electoral manipulation, one that it is a useful instrument to gain voter support and a widespread empirical phenomenon, the other that voters punish rather than reward fiscal manipulation.     

Finding common seasonal patterns among time series: An MDS approach

This paper provides an approach to the analysis of time series seasonal pattern similarities based on a special MDS approach — the non-metric SSA-I (Smallest Space Analysis) technique. Indices of dissimilarity for time series are defined generally while special cases drawn from the economic problems are treated by means of examples. The basic contributions of the paper are two-fold: First we extend the use of SSA-I to time series analysis by transforming the mutual relationship between (as well as within) the time series in a symmetric matrix. As a result, the tool of SSA-I developed by L. Guttman may easily be used. Second, by an introduction of non-metric techniques such as SSA-I in time series analysis we increase our capacity to deal with problems hitherto unsolved. In particular, ordinal data as well as behavioral data for which model processes are not defined and seasonal patterns similarities may be studied by our technique.     

Exploring the relationship between visitor attractions and events: definitions and management factors

The growing definitional debate on the terms ‘visitor attractions’ and ‘events’ highlights the need to compare their key determinants and management factors. The article elaborates on this definitional debate, by exploring existing definitions and developing an illustration of a continuum between visitor attractions and events. This is followed by a comparison of the management factors and key criteria in the effective management of visitor attractions and events. The findings indicate that while there are many similarities between the sectors, aspects such as spatio-temporality and levels of integration with the visitor attraction nucleus are identified as factors that differentiate them. In conclusion, the article determines that events should be examined separately from the visitor attraction sector due to their differing perspectives, measures, and management needs.     

A note on factor analysis and arbitrage pricing theory

This paper examines some theoretical and empirical properties of factor analysis and spells out their implications for Arbitrage Pricing Theory (APT). Doubts on the appropriateness of conventional factor analytic procedures for testing APT are raised on theoretical as well as empirical grounds.     

Does the Diversification–Firm Performance Relationship Change Over Time? A Meta‐Analytical Review

We study the relationship between diversification and firm performance in the context of the decline in levels of diversification over time. We argue that the pressure to reduce diversification may have more strongly affected those firms whose diversification strategies were most detrimental to firm performance. We employ meta‐analytical regression (MARA) in order to test our hypotheses, using a total of 267 primary studies containing 387 effect sizes based on 150,000 firm‐level observations from over 60 years of research on the diversification–firm performance relationship. The findings suggest that levels of unrelated diversification have decreased, whereas levels of related diversification have increased since the mid‐1990s, following an initial decrease in the 1970s and 1980s. Furthermore, we find that the relationship between unrelated diversification and firm performance has improved significantly over time, whereas the relationship between related diversification and performance has remained relatively stable.     

Modeling exchange rate return volatility of RMB/USD using GARCH family models

The paper examines volatility of RMB exchange rate return of onshore and offshore markets. The onshore rate covered 4/01/2008–5/09/2016 while offshore spanned 31/12/2008-22/09/2016, the returns were not normally distributed and were integrated of order zero I(0). The Ljung-Box Q statistics depicts the presence of autocorrelation in return series and Ljung-Box Q² statistics of power transformed for conditional heteroscedasticity for lags of 6, 12 and 20 all indicated the presence of conditional heteroscedascity. The exchange rates volatility was persistent in both markets. However, offshore return was more persistent while leverage effects exist in both markets. Asymmetry power Autoregressive conditional Heteroscedastic (APARCH) model was the best model for forecasting purposes in both markets while Glosten, Jogannathan and Rankle, Generalized Autoregressive conditional Heteroscedastic (GJR-GARCH) model and Integrated Generalized Autoregressive conditional Heteroscedastic (I-GARCH) were the worst models in onshore and offshore return markets respectively. APARCH model should be adopted for future studies.