On the distributional effects of income in an aggregate consumption relation

Abstract .  In this paper we analyse the influence of characteristics of the income distribution in modelling aggregate consumption expenditure. We model the aggregate consumption relation of a heterogeneous population, using a statistical distributional approach of aggregation, and apply it to UK-Family Expenditure Survey data. A bootstrap test based on a non-parametric estimation methodology, which accounts for the presence of continuous and discrete variables, suggests that the mean and the dispersion of the income distribution significantly influence aggregate consumption expenditure. Also, the parameters of the aggregate relation are time varying. These findings have implications for constructing empirically sound models of aggregate consumption expenditure.     

How should Engel's law be formulated?

Engel's law expresses a “negative stochastic association” of income and the proportion of income that is spent on food. However, there are many quite different notions of “negative stochastic association” and consequently there are different ways of defining Engel's law. We relate these different concepts to Engel's original statistical analysis and show that one must give credit to Engel for the first non-parametric statistical analysis of budget-data.     

Credit Contagion Channels: Market Microstructure Evidence from Lehman Brothers’ Bankruptcy

Immediately after Lehman Brothers’ bankruptcy, many firms disclosed their financial exposure (or lack thereof) to Lehman. This offers a clean setting to test two credit contagion channels through which a financial firm's bankruptcy can affect other firms—“counterparty risk” and “information transmission” channels. Using market microstructure variables to measure the various dimensions of contagion effects, we provide robust evidence supporting the significance of counterparty risk. Firms with exposure to Lehman suffered more severe negative effects—wider bid‐ask spread, higher price impact, greater information asymmetry, and greater selling pressure—than unexposed firms. We find mixed evidence regarding the information transmission hypothesis.     

Is education the panacea for economic deprivation of Muslims?: Evidence from wage earners in India, 1987–2005

Few researchers have examined the nature and determinants of earnings differentials among religious groups, and none has been undertaken in the context of conflict-prone multi-religious societies like the one in India. We address this lacuna in the literature by examining the differences in the average log earnings of Hindu and Muslim wage earners in India, during the 1987–2005 period. Our results indicate that education differences between Hindu and Muslim wage earners, especially differences in the proportion of wage earners with tertiary education, are largely responsible for the differences in the average log earnings of the two religious groups across the years. By contrast, differences in the returns to education do not explain the aforementioned difference in average log earnings. In conclusion, we discuss some policy implications.     

Management Risk Incentives and the Readability of Corporate Disclosures

Managers with higher risk incentives (greater options vega) issue less readable disclosures. Firms in the top quartile of vega file annual reports that are about 15.4% more voluminous than those in the bottom quartile. The effect of vega on obfuscation remains after controlling for firm risk, operating complexities, accounting and auditor choices, chief executive officer changes, and an exogenous shock to option compensation. This effect is tempered by higher institutional ownership, lower management entrenchment, and greater analyst following. Obfuscation benefits managers by increasing return volatility (option value) and allowing greater earnings management. These findings document a new link between options and disclosure transparency.     

DO DEALERS INFER INFORMATION FROM ORDER FLOW?

I examine strategic behavior among dealers in the NASDAQ market and document that there is a lead quote‐setting dealer in each security and that the quotes posted by this leader are informative. Other dealers free‐ride this information by following the lead quote‐setting dealer. The lead dealer can be identified by two information signals: (1) percentage of time spent on the inside market (i.e., posting inside quotes), and (2) trade volume transacted. Dealers that free‐ride the leader's quotes quickly update their posted quotes in the same direction as the leader's quote change. My findings suggest that directing trade to the lead dealer may be more advantageous than randomly routing trade.     

Trade classification algorithms for electronic communications network trades

Ellis et al. [Ellis, K., Michaely, R., O’Hara, M., 2000. The accuracy of trade classification rules: Evidence from Nasdaq. Journal of Financial and Quantitative Analysis 35 (4), 529–551] find that trade classification rules have limited success in classifying trades which execute inside the quotes. We reconfirm this result and propose an alternative algorithm to improve the classification accuracy for trades inside the quotes. This alternative algorithm improves the overall success rate for classifying trades, especially for trades that occur inside the quotes. Additionally, we show that the Lee and Ready [Lee, C., Ready, M., 1991. Inferring trade direction from intraday data. Journal of Finance 46, 733–747] and Ellis et al. (2000) trade classification algorithms provide biased estimates of the actual effective spreads and price impacts, while our algorithm provides statistically unbiased estimates of actual effective spreads and price impacts.     

Institutionalizing Ethics in Institutional Voids: Building Positive Ethical Strength to Serve Women Microfinance Borrowers in Negative Contexts

This study examines whether microfinance institutions (MFIs) that serve women borrowers at the base of the economic pyramid are likely to adopt a written code of positive organizational ethics (POE). Using econometric analysis of operational and economic data of a sample of MFIs from across the world, we find that two contextual factors—poverty level and lack of women’s empowerment—moderate the influence of an MFI’s percentage of women borrowers on the probability of the MFI having a POE code. MFIs that serve more women borrowers are more likely to adopt a POE code, especially in negative contexts (where women borrowers face poverty and disempowerment and are therefore susceptible to abuse). This study provides evidence that MFIs can build positive ethical strength in negative contexts.     

MOMENTUM: DOES THE DATABASE MAKE A DIFFERENCE?

We examine discrepancies between the Center for Research in Security Prices (CRSP) and Trade and Quote (TAQ) databases by examining the returns of momentum strategies using each database. Momentum portfolios constructed from CRSP prices earn significant profits whereas similar portfolios using TAQ prices show losses. Adjusting TAQ prices with the TAQ dividends file or with the cumulative distribution factor provided by CRSP does not eliminate all differences. There are significant discrepancies in the way CRSP and TAQ record newly listed and delisted stocks. We document the residual (after all filters) price differences between the two databases and provide filters to adjust TAQ data for long sample periods and large sample sizes. Our filtering procedures allow for the possibility of examining intraday patterns in momentum profits.