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The idea that a bank's overall performance is influenced by the regional economy in which it operates is intuitive and broadly consistent with historical bank performance. Yet, micro-level research on the topic has borne mixed results, failing to find a consistent link between various measures of bank performance and regional economic variables. This chapter attempts to reconcile the intuition with the micro-level data by aggregating bank performance, as measured by nonperforming loans, up to the state level. This level of aggregation reduces the influence of idiosyncratic bank effects sufficiently so as to examine more clearly the influence of state-level economic variables. We show that regional variables, such as employment growth and changes in real estate prices, are not particularly useful for predicting changes in bank performance, but that coincident indicators developed to track a state's gross output are quite useful. We find that these coincident indicators have a statistically significant and economically important influence on state-level, aggregate bank performance. In addition, the coincident indicators potentially contribute to the out-of-sample forecasts of the relative riskiness of state-level bank portfolios, which should be of interest to bankers and bank supervisors.

This research examines the use of econometric models to predict the total net asset value (NAV) of an asset allocation mutual fund. In particular, the mutual fund case used is the Vanguard Wellington Fund (VWELX). This fund maintains a balance between relatively conservative stocks and bonds. The period of the study on which the prediction of the total NAV is based is the 24-month period of 2010 and 2011 and the forecasting period is the first three months of 2012. Forecasting the total NAV of a massive conservative allocation fund, composed of an extremely large number of investments, requires a method that produces accurate results. Achieving this accuracy has no necessary relationship to the complexity of the methods typically employed in many financial forecasting studies.

Purpose – This chapter investigates the influence of bank loan underwriting practices on loan losses and identifies potential determinants of lending practices for five categories of loans: business, consumer, commercial real estate, home equity, and construction and land development loans.

Methodology/approach – Using data on the riskiness of lending practices obtained from the U.S. Federal Deposit Insurance Corporation (FDIC) bank examiner surveys from January 1996 to March 2009, I fit a two-step treatment effects model to measure the effects of underwriting practices on loan losses, controlling for the potential endogeneity of lending practices.

Findings – In the selection step, I find that for business loans, the likelihood that bank management will adopt low-risk lending practices increases with bank financial performance and management quality hierarchical complexity and decreases with market competition. Results for the selection of lending practices for consumer loans and three categories of real estate loans are similar to those found for business loans but show weaker statistical relationships to all explanatory variables. In the loss determination step, I find that lower (higher) risk underwriting practices are generally associated with lower (higher) gross loan charge-offs (as percentage of gross loans and leases) for five categories of loans: business, consumer, commercial real estate, home equity, and construction and land development loans.

Originality/value of chapter – This is the first study to model the determinants of loan underwriting practices with the practices being characterized in terms of their risk to the bank. In addition, this is the first study to consider the effects of the riskiness of lending practices on loan losses, controlling for the endogeneity of practices.

Internal capital markets of diversified firms have been associated with inefficient allocation of investment funds across divisions, leading to value losses. Utilizing a sample of diversified firms that adopted or eliminated Residual Income (RI) plans between 1990 and 2009, we show that adoptions of these plans mitigate investment distortions and lead to value gains. Following the adoption of RI plans, diversified firms start allocating investment funds based on growth opportunities of their divisions. RI plan adopters lower their divisional investment levels, especially in segments with below-average growth opportunities. The overall investment allocation efficiency improves, and the diversification discount diminishes after the adoption of RI plans. However, RI plans appear to be used only as temporary tools for assessing corporate performance. The plans are adopted primarily by firms expected to immediately generate plan bonuses for management, and they are frequently eliminated by firms with bad accounting performance and low managerial bonuses. The study contributes to the literature on organizational efficiency, internal capital markets, and on the importance of measures based on economic profits or RI.

The central bank policy instruments have become less effective in an environment where economies are integrated with sophisticated financial products. We argue that economic stability is a function of interactions between financial and commodity markets. We utilize MGARCH models to identify volatility comovements between these markets in the United States since 2000. Our results suggest that financial markets have strong impacts on prices and volatility in commodity markets which could be due to intertemporal capital mobility. Thus, understanding commodity markets is inseparable from understanding financial market activities, and must now be included in an economic equation to achieve an effective policy.