Can countries rely on foreign saving for investment and economic development?

Contrary to widespread presumption, a surprisingly large number of countries have been able to finance a significant fraction of their investment for extended periods using foreign finance. While many of these episodes are in countries where official finance is important, we also identify episodes where a substantial fraction of domestic investment is financed by private capital inflows. Although there is evidence of a positive growth effect of such inflows in the short run, that positive impact dissipates after 5 years and turns negative over longer horizons. Many such episodes end abruptly, with compression of the current account and sharp slowdowns in investment and growth. Summing over the inflow (current account deficit) episode and its aftermath, we find that growth is slower than when countries rely on domestic savings. The implication is that financing growth and investment out of foreign savings, while not impossible, is risky and too often counterproductive.     

Dynamic managerial capabilities: Scale development and validation

Studies on dynamic managerial capabilities still have a rather theoretical nature, and there is great difficulty in finding a valid, reliable instrument to measure this construct. The present study contributes to solving this problem: It aims to develop and validate a scale to measure dynamic managerial capabilities. In this investigation, we develop a scale for three factors related to dynamic managerial capabilities: human capital, managerial cognition (already described in the literature), and relationship networks. The prominent finding in this research is the factor that is referred to here as relationship networks.     

Statistical Decision Problems and Bayesian Nonparametric Methods

This paper considers parametric statistical decision problems conducted within a Bayesian nonparametric context. Our work was motivated by the realisation that typical parametric model selection procedures are essentially incoherent. We argue that one solution to this problem is to use a flexible enough model in the first place, a model that will not be checked no matter what data arrive. Ideally, one would use a nonparametric model to describe all the uncertainty about the density function generating the data. However, parametric models are the preferred choice for many statisticians, despite the incoherence involved in model checking, incoherence that is quite often ignored for pragmatic reasons. In this paper we show how coherent parametric inference can be carried out via decision theory and Bayesian nonparametrics. None of the ingredients discussed here are new, but our main point only becomes evident when one sees all priors—even parametric ones—as measures on sets of densities as opposed to measures on finite-dimensional parameter spaces.     

Quantile serial dependence in crude oil markets: evidence from improved quantilogram analysis with quantile wild bootstrapping

We examine the quantile serial dependence in crude oil prices based on the Linton and Whang’s quantile-based portmanteau test which we improved by means of quantile wild bootstrapping (QWB). Through Monte Carlo simulation, we find that the quantile wild bootstrap-based portmanteau test performs better than the bound testing procedure suggested by Linton and Whang. We apply the improved test to examine the efficiency of two crude oil markets – WTI and Brent. We also examine if the dependence is stable via rolling sample tests. Our results show that both WTI and Brent are serially dependent in all, except the median quantiles. These findings suggest that it may be misleading to examine the efficiency of crude oil markets in terms of mean (or median) returns only. These crude oil markets are relatively more serially dependent in non-median ranges.     

Dynamics of volatility transmission between the U.S. and the Chinese agricultural futures markets

The U.S. and China are two of the biggest players in the world agricultural market. The literature documents that volatility in the U.S. agricultural futures market spills over significantly to that of China. This article provides further insights into the spillovers from China to the U.S. as well as the time horizon and dynamics of the bidirectional spillovers through the application of a multivariate extension of the heterogeneous autoregressive model, in relation to four commodities – soybean, wheat, corn and sugar. The results confirm the existence of significant spillovers from the U.S. to China for four commodities, which are primarily generated by the shorter-term volatility components in the U.S., and provide evidence for the increasing pricing power of the Chinese market. The findings are robust against various specifications and have important investment and policy implications.     

How pervasive is the effect of culture on stock market linkages? Evidence across regions and economic cycles

We conduct a comprehensive study on the effect of culture on stock market linkages. With data on 25 national stock markets, a quantile regression model is used to estimate the determinants of market linkages using culture variable/s such as language, religion and Hofstede’s cultural dimensions while controlling for distance, economic and legal variables. Further, we test whether these effects hold across regions and if changes are detected during periods of market crisis. We also test if market liquidity, an indicator of market efficiency, diminishes the impact of culture on market linkages. The main conclusion is that culture preferences shape investor choices, which affects integration between stock markets. The equity markets with similar cultural traits tend to increase market linkages; however, we observe differences across regions. Furthermore, liquidity and economic uncertainty fail to have an impact on the significance of culture variable/s as determinants of market linkages.     

Breaking the norm: An empirical investigation into the unraveling of good behavior

We present results from an artefactual field experiment conducted in rural Peru that considers whether observing non-reciprocal behavior influences an individual's decision to reciprocate. Specifically, we consider the behavior of second movers in a trust game, assessing whether their decision to reciprocate is influenced by the observed reciprocity of others. In documenting the impact of an external shock to observed reciprocity, this paper shows that small increases in non-reciprocal behavior result in an unraveling of the norm of reciprocity. Survey data is used to explore mechanisms by which this occurred. Results are not consistent with learning effects, suggesting that preferences may be changed by observing others deviating from a norm of reciprocity. These results suggest that investing in encouraging trustworthy behavior can have large benefits in situations where individuals are observing each other's behavior, such as may be the case in a new market institution.     

A Nonlinear Relationship: Unemployment and Economic Growth (Construction Sector) in Spain, 1995.1–2012.2

A quadratic version of the first-difference Okun’s Law model was estimated for Spain (1995.Q1-2012.Q2). An accelerationist version of Okun’s Law was obtained, which allowed us to calculate variable Okun coefficients as well as critical points in the relationship between construction sector growth and the variation in overall unemployment. The optimal economic growth rate was determined to be 7.38 %. By applying principal components, it is demonstrated that this sector led the economic process after 1995.     

Stock market interdependence between Australia and its trading partners: does trade intensity matter?

We investigate the extent and manner of stock market interdependence between Australia and its trading partners and examine whether this is affected by trade intensity. Based on trade intensity, we classify Australia’s trading partners into major, medium and minor partners. We hypothesize that markets with greater (lower) trade intensity will be more (less) interdependent with Australia. We perform correlation (unconditional and conditional) analyses between Australia and its trading partners. Our results indicate that most of the markets that are highly correlated with Australia are its major trading partners. We conduct panel regression analysis to investigate whether trade intensity has any impact on the stock market correlations between Australia and its trading partners. The results show that trade intensity significantly and positively affect the correlations of Australia with its major trading partners. Thus, the results confirm our hypothesis that trade intensity drives stock market interdependence between Australia and its trading partners.