On the Relationship between Market Power and Bank Risk Taking

We analyse risk-taking behaviour of banks in the context of spatial competition. Banks mobilise unsecured deposits by offering deposit rates, which they invest either in a prudent or a gambling asset. Limited liability along with high return of a successful gamble induce moral hazard at the bank level. We show that when the market power is low, banks invest in the gambling asset. On the other hand, for sufficiently high levels of market power, all banks choose the prudent asset to invest in. We further show that a merger of two neighboring banks increases the likelihood of prudent behaviour. Finally, introduction of a deposit insurance scheme exacerbates banks’ moral hazard problem.

The long run relationship between stock prices and goods prices: new evidence from panel cointegration

We examine the long run relationship between stock prices and goods prices to gauge whether stock market investment can hedge against inflation. Data from sixteen OECD countries over the period 1970-2006 are used. We account for different inflation regimes with the use of sub-sample regressions, whilst maintaining the power of tests in small sample sizes by combining time-series data across our sample countries in a panel unit root and panel cointegration econometric framework. The evidence supports a positive long-run relationship between goods prices and stock prices with the estimated goods price coefficient being in line with the generalized Fisher hypothesis.

A Bootstrap Neural Network Based Heterogeneous Panel Unit Root Test: Application to Exchange Rates

This paper proposes a bootstrap artificial neural network based panel unit root test in a dynamic heterogeneous panel context. An application to a panel of bilateral real exchange rate series with the US Dollar from the 20 major OECD countries is provided to investigate the Purchase Power Parity (PPP). The combination of neural network and bootstrapping significantly changes the findings of the economic study in favour of PPP.

Equilibrium Exchange Rate Determination and Multiple Structural Changes

The large appreciation and depreciation of the US dollar in the 1980s stimulated an important debate on the usefulness of unit root tests in the presence of structural breaks. In this paper, we propose a simple model to describe the evolution of the real exchange rate. We then propose a more general smooth transition (STR) function than has hitherto been employed, which is able to capture structural changes along the (long-run) equilibrium path, and show that this is consistent with our economic model. Our framework allows for a gradual adjustment between regimes and allows for under- and/or over-valued exchange rate adjustments. Using monthly and quarterly data for up to twenty OECD countries, we apply our methodology to investigate the univariate time series properties of CPI-based real exchange rates with both the U.S. dollar and German mark as the numeraire currencies. The empirical results show that, for more than half of the quarterly series, the evidence in favour of the stationarity of the real exchange rate was clearer in the sub-sample period post-1980.

A Comparison Of Forecasting Procedures For Macroeconomic Series: The Contribution Of Structural Break Models

This paper compares the forecasting performance of different models which have been proposed for forecasting in the presence of structural breaks. These models differ in their treatment of the break process, the parameters defining the model which applies in each regime and the out-of-sample probability of a break occurring. In an extensive empirical evaluation involving many important macroeconomic time series, we demonstrate the presence of structural breaks and their importance for forecasting in the vast majority of cases. However, we find no single forecasting model consistently works best in the presence of structural breaks. In many cases, the formal modeling of the break process is important in achieving good forecast performance. However, there are also many cases where simple, rolling OLS forecasts perform well.

A Comparison Of Forecasting Procedures For Macroeconomic Series: The Contribution Of Structural Break Models

This paper compares the forecasting performance of different models which have been proposed for forecasting in the presence of structural breaks. These models differ in their treatment of the break process, the parameters defining the model which applies in each regime and the out-of-sample probability of a break occurring. In an extensive empirical evaluation involving many important macroeconomic time series, we demonstrate the presence of structural breaks and their importance for forecasting in the vast majority of cases. However, we find no single forecasting model consistently works best in the presence of structural breaks. In many cases, the formal modeling of the break process is important in achieving good forecast performance. However, there are also many cases where simple, rolling OLS forecasts perform well.

The economics of power and control

John Hardman Moore outlines his joint research with Oliver Hart, looking at the economics of power and control and the foundations of contractual incompleteness

Relationship between trade openness and economic growth of India: A time series analysis

The paper aims to examine the empirical relationship between trade openness and economic growth of India for the time period 1970-2010. Trade openness is a multi-dimensional concept and hence measures of both trade barriers and trade volumes have been used as proxies for openness. The estimation results from Vector Autoregressive method suggest that growth in trade volumes accelerate economic growth in case of India. We do not find any evidence from our analysis that trade barriers lower growth.

Factors Affecting the Financial Success of Motion Pictures: What is the Role of Star Power?

In the mid-1940s, American film industry was on its way up to its golden era as studios started mass-producing iconic feature films. The escalating increase in popularity of Hollywood stars was actively suggested for its direct links to box office success by academics. Using data collected in 2007, this paper carries out an empirical investigation on how different factors, including star power, affect the revenue of ‘home-run’ movies in Hollywood. Due to the subjective nature of star power, two different approaches were used: (1) number of nominations and wins of Academy Awards by the key players, and (2) average lifetime gross revenue of films involving the key players preceding the sample year. It is found that number of Academy awards nominations and wins was not statistically significant in generating box office revenue, whereas star power based on the second approach was statistically significant. Other significant factors were critics’ reviews, screen coverage and top distributor, while number of Academy awards, MPAA-rating, seasonality, being a sequel and popular genre were not statistically significant.