The dynamics of industrial concentration in Australian manufacturing

A dynamic model of concentration is developed, with incomplete and industry-specific adjustment to deviations of concentration from its steady state. Cross-sectional analysis is carried out against a sample of 102 Australian manufacturing industries at the Australian Standard Industrial Classification (ASIC) four-digit level over the period 1977/78–1984/85. The estimated adjustment is faster than found in studies of the more mature industrial economies and this adjustment is found to significantly increase with reductions in tariff protection. There is also empirical support for John Sutton's argument that the relationship between concentration and market size depends on whether set-up costs are exogenous.     

Heterogeneity,impatience, and dynamic private provision of a discrete public good

We analyze dynamic private provision of a discrete public good by heterogeneous agents, who differ in terms of their levels of impatience, in a differential game framework. In contrast to the strategic complementarity result for homogeneous individuals, we show that an asymmetric completion Markov perfect equilibrium exists, where the individual contributions and the strategic behaviors depend crucially on an impatience differential: the difference in rates of time preference across groups of individuals. When this differential is insignificant, contributions of both types of individuals are strategic complements. On the other hand, when this impatience differential exceeds a threshold, the contributions of impatient individuals become strategic substitutes, whereas the contributions of patient individuals remain strategic complements. We show that group size has an interesting role to play in the strategic behavior: increasing the number of patient individuals aggravates the incentives to free‐ride by the impatient agents. We also derive a condition under which all the socially beneficial projects get completed in the equilibrium.     

The relationship between the marketing mix and share of category requirements

A criticism of purchase-based brand loyalty measures is that they are confounded by the marketing mix variables that affect brand choice. This paper investigates the magnitude and direction of the associations for share of category requirements (SCR), defined as each brand's share among the group of households who bought the brand at least once during the time period under consideration. We discuss the theoretical foundations for the relationships between SCR and a set of marketing mix variables (price, promotions, retail distribution) and conduct a latent structure regression analysis of brand-level data to test these relationships. We find that, although the relationship between the marketing mix variables and SCR is statistically significant, in real terms the magnitude of the association is fairly low.     

Herding by mutual funds: impact on performance and investors’ response†

In this paper we investigate whether herding by actively managed equity funds affects their performances and flows over the 1980–2013 period. We show that during the herding quarter, on average, funds that trade with the herd benefit from this behavior. Although this does not directly translate into a positive association between the extent to which funds herd and their subsequent performance, we find that the funds that follow the herd earn negative abnormal returns whereas the ones that lead earn no abnormal returns. Our results also indicate that investors react adversely to follower funds while they are neutral towards the leader funds.     

Drivers and impact of food inflation in India

Average food inflation in India during 2006–2013 was one of the highest among emerging market economies, and nearly double the inflation witnessed in India during the previous decade. In this paper, we analyse the behaviour and determinants of food inflation over the recent past. Our main findings include that recent surge in food inflation in India is a result of various factors. On the cost side, agricultural wage inflation is found to be a universal driver of food commodities inflation, as well as the aggregate food inflation. The contribution of agricultural wages has increased significantly in the post Mahatma Gandhi National Rural Employment Act era. Fuel inflation has a moderate impact on food inflation and the effects vary across commodities. Our analysis indicates limited role of fuel and international prices, except for in tradeables. Finally, results suggest significant pass-through effects from food to non-food and to the headline inflation.     

Political regimes and financial crises

This study investigates how democratic or autocratic regimes, their transitions, and durations, affect the probability of experiencing financial crises. The empirical strategy employs novel instruments and Lewbel's method to address potential endogeneity concerns. The results reveal that democratic transition reduces the probability of crises by around seven percent, whereas autocratic switchovers enhance the crises likelihood by twelve percent. The findings remain robust in presence of a number of heterogeneity checks, with alternative measures of crises indicators, and employing different proxy for democratic transition. Thus, institutions in transition countries could play important role in managing such financial upheavals.     

Nowcasting India’s Quarterly GDP Growth: A Factor-Augmented Time-Varying Coefficient Regression Model (FA-TVCRM)

Governments, central banks, private firms and others need high frequency information on the state of the economy for their decision making. However, a key indicator like GDP is only available quarterly and that too with a lag. Hence decision makers use high frequency daily, weekly or monthly information to project GDP growth in a given quarter. This method, known as nowcasting, started out in advanced country central banks using bridge models. Nowcasting is now based on more advanced techniques, mostly dynamic factor models. In this paper we use a novel approach, a Factor Augmented Time Varying Coefficient Regression (FA-TVCR) model, which allows us to extract information from a large number of high frequency indicators and at the same time inherently addresses the issue of frequent structural breaks encountered in Indian GDP growth. One specification of the FA-TVCR model is estimated using 19 variables available for a long period starting in 2007–08:Q1. Another specification estimates the model using a larger set of 28 indicators available for a shorter period starting in 2015–16:Q1. Comparing our model with two alternative models, we find that the FA-TVCR model outperforms a Dynamic Factor Model (DFM) model and a univariate Autoregressive Integrated Moving Average (ARIMA) model in terms of both in-sample and out-of-sample Root Mean Square Error (RMSE). Further, comparing the predictive power of the three models using the Diebold-Mariano test, we find that FA-TVCR model outperforms DFM consistently. In terms of out-of-sample forecast accuracy both the FA-TVCR model and the ARIMA model have the same predictive accuracy under normal conditions. However, the FA-TVCR model outperforms the ARIMA model when applied for nowcasting in periods of major shocks like the Covid–19 shock of 2020–21.

     

Can short sellers constrain aggressive non-GAAP reporting?

Review of Accounting Studies - Prior research finds an association between short selling volume and aggressive non-GAAP earnings disclosures but does not explore whether increased short selling...