THE LOCATION OF NONMETROPOLITAN HIGH-TECH INDUSTRIES: A Comparison of Regional Determinants

A study of the location of three classifications of high-tech industries in rural areas was undertaken using ordinary least squares, Tobit, and a two-step estimation procedure suggested by Heckman (1976). The results indicate that the location decision for high tech firms is influenced primarily by the county population, adjacency to an SMSA, and the expenditures on public infrastructure (exclusive of education expenditures). However, location near interstate highways was generally not a significant factor. Results were similar between branch and unit (single ownership) plants. Some differences in signs of orders of magnitude occurred among the estimation procedures. Making a choice between Tobit and Heckman approaches depends upon the goal of the research.     

ENTREPRENEURSHIP AND THE SMALL FIRM: A REVIEW ARTICLE

H erbert G iersch (ed.) New Opportunities for Entrepreneurship . Tübingen: Mohr, 1984, pp. 262 + vi, DM62 (paperback). C yril L evicki     

Fragmentation, Engel's Law, and Learning

This paper outlines the conditions under which trade is beneficial for a developing country's growth. A developing country suffers from two disadvantages: low income and a comparative disadvantage in the production of modern manufactured goods—goods which allow a high rate of human capital accumulation through learning by doing. Low income together with Engel's law imply that developing countries consume and produce very few modern goods in autarky and hence grow slowly. With international fragmentation of production, a developing country may find comparative advantage in the production of some stages of modern goods despite an absence of comparative advantage in the production of modern goods under “100% local content.” More resources can then be allocated to the modern goods sector leading to greater learning externalities and hence growth under free trade than in autarky.     

Stock Market Reactions to SFAS No. 96: Evidence from Early Bank Adopters

Statement of Financial Accounting Standards (SFAS) No. 96, “Accounting for Income Taxes,” issued by the Financial Accounting Standards Board (FASB) in December 1987 changed accounting for income tax recognition and accrual. The original deadline for implementation of SFAS No. 96 was December 15, 1988, and earlier adoption was encouraged. This study examines empirically the stock price impact of four pertinent announcement dates regarding SFAS No. 96 for 19 banks that adopted the statement in late 1987 and early 1988. Our results suggest that these early bank adopters have different characteristics from other banks that cause them to benefit from the changes in accounting for deferred taxes and explain their voluntary adoption of the standard.     

Measuring Integrated Market and Credit Risk in Bank Portfolios: An Application to a Set of Hypothetical Banks Operating in South Africa

The banking crises of the ‘90s emphasize the need to model the connections between financial environment volatility and the potential losses faced by financial institutions resulting from correlated market and credit risks. Due to the number of variables that must be modeled and the complexity of the relationships an analytical solution is not feasible. We present here a numerical solution based on a simulation model that explicitly links changes in the relevant variables that characterize the financial environment and the distribution of possible future bank capital ratios. This forward looking quantitative risk assessment methodology allows banks and regulators to identify potential risks before they materialize and make appropriate adjustments to bank portfolio credit qualities, sector and region concentrations, and capital ratios on a bank by bank basis. It also has the potential to be extended so as to assess the risks of correlated failures among a group of financial institutions (i.e., systemic risk analyses). This model was applied by the authors to the study of the risk profile of the largest South African Banks in the context of the Financial System Stability Assessment program undertaken by the IMF in 1999. In the current study, we apply the model to various hypothetical banks operating in the South African financial environment and assess the correlated market and credit risks associated with business lending, mortgage lending, asset and liability maturity matches, foreign lending and borrowing, and direct equity, real estate, and gold investments. It is shown to produce simulated financial environments (interest rates, exchange rates, equity indices, real estate price indices, commodity prices, and economic indicators) that match closely the assumed parameters, and generate reasonable credit transition probabilities and security prices. As expected, the credit quality and diversification characteristics of the loan portfolio, asset and liability maturity mismatches, and financial environment volatility, are shown to interact to determine bank risk levels. We find that the credit quality of a bank's loan portfolio is the most important risk factor. We also show the risk reduction benefits of diversifying the loan portfolio across various sectors and regions of the economy and the importance of accounting for volatility shocks that occur periodically in emerging economies. Banks with high credit risk and concentrated portfolios are shown to have a high risk of failure during periods of financial stress. Alternatively, banks with lower credit risk and broadly diversified loan portfolios across business and mortgage lending are unlikely to fail even during very volatile periods. Asset and liability maturity mismatches generally increase bank risk levels. However, because credit losses are positively correlated with interest rate increases, banks with high credit risk may reduce overall risk levels by holding liabilities with longer maturities than their assets. Risk assessment methodologies which measure market and credit risk separately do not capture these various interactions and thus misestimate overall risk levels.