Fuelled Power: Oil,Financiers and Central Bank Policy in Nigeria

While the literature on business power and global finance has illuminated the ways in which financial institutions limit the policy autonomy of states in developing countries, we know much less about the circumstances under which the power of financiers is undermined. In this article, I advance explanations of these circumstances by arguing that state access to natural resource revenues reduces the power of financial institutions and enhances the capacity of the state to pursue central bank policies which violate the interests of major financiers. I employ a case study of central bank policy in Nigeria to probe this argument and find evidence that supports the claim that whenever the Nigerian government's access to resource revenues increased, the state's capacity to diverge from financiers’ preferred central bank policies and to advance its own preferences increased as well. The analysis provides the basis for broader propositions about the policy space of developing countries vis-à-vis financial institutions and the variability of structural power.     

Do GCC market-oriented labor policies encourage inward FDI flows?

In this paper, we empirically examine the impact of market-oriented labor policies on inward FDI flows to the GCC countries. The paper adopts different estimation methodologies to address endogeneity and cross-sectional dependence. Reliance on professional management reduces inward FDI flows to the UAE while linking pay to productivity reduces inward FDI flows to both Bahrain and the UAE. Trade openness and infrastructure development have a positive influence, while human capital development has a surprisingly negative influence. Evidence, therefore, does not support the view that flexible labor market policies encourage inward FDI flows to GCC countries.     

Is real per capita state personal income stationary? New nonlinear,asymmetric panel-data evidence

This paper re-examines the stochastic properties of U.S. state real per capita personal income, using new panel unit-root procedures. The new developments incorporate non-linearity, asymmetry, and cross-sectional correlation within panel-data estimation. Including nonlinearity and asymmetry finds that 43 states exhibit stationary real per capita personal income whereas including only nonlinearity produces 42 states that exhibit stationarity. Stated differently, we find that two states exhibit nonstationary real per capita personal income when considering nonlinearity, asymmetry, and cross-sectional dependence.     

Empirical evidence of extreme dependence and contagion risk between main cryptocurrencies

This study examines the dependence and contagion risk between Bitcoin (BTC), Litecoin (LTC) and Ripple (XRP) using non-parametric mixture copulas (developed by Zimmer, 2012) and recently proposed methods of full-range tail dependence copulas (advanced by Hua, 2017, Su and Hua, 2017), for the period from 04-08-2013 to 17-06-2018. The Chi-plots and Kendall plots results show heavy tail dependence between each pairs of the cryptocurrencies. Evidence from the mixture copula indicates that for the BTC-LTC pair the upper-tail dependence is both stronger and more prevalent, while for the other pairs of cryptocurrencies the lower-tail dependence is very strong and more prevalent. However, the results of the full-range tail dependence copulas reveal a strong and prevalent upper and lower-tail dependence of each pairs of cryptocurrencies. These results provide evidence of significant risk contagion among price returns of major cryptocurrencies, both in bull and bear markets.     

Forecasting portfolio-Value-at-Risk with nonparametric lower tail dependence estimates

We propose to forecast the Value-at-Risk of bivariate portfolios using copulas which are calibrated on the basis of nonparametric sample estimates of the coefficient of lower tail dependence. We compare our proposed method to a conventional copula-GARCH model where the parameter of a Clayton copula is estimated via Canonical Maximum-Likelihood. The superiority of our proposed model is exemplified by analyzing a data sample of nine different bivariate and one nine-dimensional financial portfolio. A comparison of the out-of-sample forecasting accuracy of both models confirms that our model yields economically significantly better Value-at-Risk forecasts than the competing parametric calibration strategy.     

Forecasting using heterogeneous panels with cross-sectional dependence

In this paper, we focus on forecasting methods that use heterogeneous panels in the presence of cross-sectional dependence in terms of both spatial error dependence and common factors. We propose two main approaches to estimating the factor structure: a residuals-based approach, and an approach that uses a panel of auxiliary variables to extract the factors. Small sample properties of the proposed methods are investigated through Monte Carlo simulations and applied to predict house price inflation in OECD countries.     

Stock market reactions to domestic sentiment: Panel CS-ARDL evidence

This study sets out to explore the effects of business and consumer sentiment on stock market performance, within the separate contexts of advanced and emerging markets. The empirical analysis is carried out using the cross-sectionally augmented autoregressive distributed lag (CS-ARDL) modeling approach, which considers time dynamics, cross-sectional heterogeneity, and cross-sectional dependence. The findings for developed markets suggest that business sentiment has positive leading effects on stock returns, across short- and long-term time horizons, while for emerging markets, the price impact of business sentiment turns out to be short-lived. On the other hand, consumer sentiment tends to affect positively both market types, albeit only in the short run. Furthermore, the influence of sentiment indicators seems to be stronger in emerging- than in developed-market countries. The results remain robust, even after controlling for a rich range of potential predictors of stock returns. Generally, such evidence highlights the relevance of psychological factors, such as business and consumer sentiment, in determining the future trajectory of asset prices.     

The effects of board structure on corporate performance: Evidence from East African frontier markets

The effectiveness of the well-known corporate governance practices may not be universal due to fundamental differences in the environments under which firms operate. By using hand-collected data from all the non-financial firms listed on the unexplored East African frontier markets (i.e., Kenya, Tanzania and Uganda), we examine the effect of board characteristics on the performance of firms. Our results show that board size has a negative and significant effect on firm performance. The presences of foreigners and civil servants on the board play positive roles on financial performance, where the agency and resource dependence theories apply. Further, we find that board members with higher education also contribute to firm performance. These findings still hold when we consider the 2008–2009 financial crisis period. Overall, we show that in a business climate where ownership is largely dominated by few shareholders, the conventional governance mechanisms do not work effectively.     

How do institutional market players matter in farmland pricing?

In this paper we analyse how institutional sellers within the privatisation process shape price formation in agricultural land markets by taking the German reunification as an example. These institutions sell the formerly state owned land within first-price sealed bid auctions, publish calls and obtained prices, and are hypothesised to exploit their market power. Based on the conceptual framework of hedonic pricing models, we use a spatio-temporal modelling approach to empirically quantify these impacts. We thereby control for land productivity characteristics, potential buyers and whether farmers purchase the land. We find that privatisation agencies sell at significantly higher prices, while one agency sells at lower prices to farmers.     

State dependence in access to credit

This paper investigates whether firms’ access to credit is characterized by state dependence. We introduce a first-order Markov model of credit restriction with sample selection that makes it possible to identify state dependence in presence of unobserved heterogeneity. The results, based on a representative sample of Italian firms, show that state dependence in access to credit is a statistically and economically significant phenomenon and that this is more prominent among medium-large firms.