This paper presents a statistical procedure to identify effects of three potential structural changes on accounting earnings – temporary, short-run, and long-run. The procedure is applied to quarterly accounting earnings of 39 utility companies. Structural changes are found to be commonplace. Statistical forecasting models that explicitly incorporate structural change effects are found to generate more accurate forecasts than other statistical models in the literature. Although no statistical model significantly dominates Value Line, a firm-specific model with structural change adjustment forecasts as well as Value Line. Moreover, all statistical models examined have significant marginal forecasting power to complement Value Line forecasts.

We applied the VARMA test to examine the dynamic relation between prices and interest rates. The dynamic relation, which is important to characterize the nature of the Gibson paradox, provides economists new insight in discriminating against competing theories. In light of our empirical findings, all theories in the literature lose their persuasiveness. We found some evidence of unidirectional relation from prices to interest rates, but we found no evidence of unidirectional relation from interest rates to prices. Hence, the business cycle explanations advanced by Wicksell (1907), Keynes (1930), Lee and Petruzzi (1986), and Barsky and Summers (1988) are especially in jeopardy. A century and a half after its birth, this paradox is more puzzling than ever.

One question development economists are especially interested in, but so far left unanswered, is: how would the societal income distribution be affected by introducing a family-planning program to reduce the reproduction rate of the poor, which is usually high in developing countries? The purpose of this paper is to search for analytical answers to this question. We are able to make definite comparisons about some class of inequality measures of the steady-state societal income distributions, and these comparisons provide strong theoretical support in favor of the above-mentioned family-planning program.

This paper defines and tests a form of market efficiency called market dexterity which requires that asset prices adjust instantaneously and completely in response to new information. Examining the behavior of the yen/dollar exchange rate while each of the major markets are open it is possible to test for informational effects from one market to the next. Assuming that news has only country specific autocorrelation such as a heat wave. any intra-daily volatility spillovers (meteor showers) become evidence against market dexterity. ARCH models are employed to model heteroskedasticity across intra-daily market segments. Statistical tests lead to the rejection of the heat wave and therefore the market dexterity hypothesis. Using a volatility type of vector autoregression we examine the impact of news in one market on the time path of volatility in other markets.