On the Value Relevance of Retailer Advertising Spending and Same-store Sales Growth

In response to recent calls to study factors that determine a retailer's stock price, this study draws on signaling theory to examine the impact of two key marketing metrics that are widely disclosed by retailers to investors, advertising spending and growth in same-store sales (COMPS), and highlights the moderating role of various firm- and sector-specific factors. Using a stock-response model estimated on a sample of 1,646 observations for 257 retailers, the authors find that the value relevance of advertising spending and COMPS depends on the financial condition of, and the competitive pressures faced by, the retailer. In addition, the positive effect of COMPS on stock returns is found to be stronger in the presence of decreases in advertising spending.     

Optimal certification policy,entry, and investment in the presence of public signals

We explore the optimal disclosure policy of a certification intermediary where (i) the seller decides on entry and investment in product quality, and (ii) the buyers observe an additional public signal on quality. The optimal policy maximizes rent extraction from the seller by trading off incentives for entry and investment. We identify conditions under which full, partial or no disclosure can be optimal. The intermediary's report becomes noisier as the public signal gets more precise, but if the public signal is sufficiently precise, the intermediary resorts to full disclosure. However, the social welfare may reduce when the public signal becomes more informative.     

Product market competition, open shop union and wage

We show that if the product market is not very much concentrated, open shop union, where the union density is less than one, may not be a justification for a positive relationship between product market competition and unionized wage, irrespective of the union density, bargaining power of the union and the union??s preference for wage and employment.     

Managing internationalization and innovation tradeoffs in entrepreneurial firms: Evidence from transition economies

For entrepreneurial firms (EFs), internationalization and innovation present two major avenues for growth. Prior research, based primarily on EFs from advanced economies, demonstrates mixed insights for the relationship between these strategies. A deeper understanding of the tradeoffs involved in the internationalization-innovation relationship may help better comprehend the issue. In this study, we draw on the organizational learning and capabilities-based literatures to examine the relationship in the context of EFs in transition economies (EFTEs). Our findings suggest that in EFTEs, internationalization is negatively associated with the likelihood of innovation. We also find that three knowledge-based capabilities of EFTEs (absorptive capacity, appropriation capability, and managerial capability) positively moderate the aforementioned negative relationship. We do not find any evidence of reverse causality (EFTE innovation impacting internationalization). Our research provides novel insights to the IE literature by shedding light on the internationalization–innovation tradeoffs that EFTEs experience.     

Managing the Impact of a Mutating Global Crisis on Organizations

Atlantic Economic Journal -     

Covariate and Idiosyncratic Shocks and Coping Strategies for Poor and Non-poor Rural Households in India

The objective of the paper is to track the association between different type of shocks experienced by rural households and corresponding coping strategies opted by them as they are, not only exposed to household-level and community level shocks, but also, lack effective risk management strategies which make them vulnerable to get into chronic poverty. A probit analysis has been used to articulate the comparative static distinction of risk management strategies between poor and non poor rural households using Additional Rural Incomes Survey/Rural Economic and Demographic Survey (ARIS/REDS) data surveyed by National Council of Applied Economic Research (NCAER) in rural India across 17 states to get a comparative static analysis. Households, generally, withdraw savings, seek remittances from migrant family members, take loan from formal and informal lenders and sell their existing assets and participate in Government sponsored welfare based programs to control after effect of shocks. Comparatively non-poor rural households could build up safety net (precautionary measure) to cope with price rise and other sudden shocks. But, extremely poor, generally, if don’t get help from relatives or can’t borrow from informal sources, ultimately starve at the time of sudden shocks. The welfare based government programs fail to arrest this extreme situation of grief during the idiosyncratic shocks.

     

Semiparametric binary regression models under shape constraints with an application to Indian schooling data

We consider estimation of the regression function in a semiparametric binary regression model defined through an appropriate link function (with emphasis on the logistic link) using likelihood-ratio based inversion. The dichotomous response variable Δ$\Delta$ is influenced by a set of covariates that can be partitioned as (X,Z)$(X,Z)$ where Z$Z$ (real valued) is the covariate of primary interest and X$X$ (vector valued) denotes a set of control variables. For any fixed X$X$, the conditional probability of the event of interest (Δ=1$\Delta =1$) is assumed to be a non-decreasing function of Z$Z$. The effect of the control variables is captured by a regression parameter β$\beta$. We show that the baseline conditional probability function (corresponding to X=0$X=0$) can be estimated by isotonic regression procedures and develop a likelihood ratio based method for constructing asymptotic confidence intervals for the conditional probability function (the regression function) that avoids the need to estimate nuisance parameters. Interestingly enough, the calibration of the likelihood ratio based confidence sets for the regression function no longer involves the usual χ²${\chi }^2$ quantiles, but those of the distribution of a new random variable that can be characterized as a functional of convex minorants of Brownian motion with quadratic drift. Confidence sets for the regression parameter β$\beta$ can however be constructed using asymptotically χ²${\chi }^2$ likelihood ratio statistics. The finite sample performance of the methods are assessed via a simulation study. The techniques of the paper are applied to data sets on primary school attendance among children belonging to different socio-economic groups in rural India.     

Deep networks for predicting direction of change in foreign exchange rates

Trillions of dollars are traded daily on the foreign exchange (forex) market, making it the largest financial market in the world. Accurate forecasting of forex rates is a necessary element in any effective hedging or speculation strategy in the forex market. Time series models and shallow neural networks provide acceptable point estimates for future rates but are poor at predicting the direction of change and, hence, are not very useful for supporting profitable trading strategies. Machine learning classifiers trained on input features crafted based on domain knowledge produce marginally better results. The recent success of deep networks is partially attributable to their ability to learn abstract features from raw data. This motivates us to investigate the ability of deep convolution neural networks to predict the direction of change in forex rates. Exchange rates for the currency pairs EUR/USD, GBP/USD and JPY/USD are used in experiments. Results demonstrate that trained deep networks achieve satisfactory out‐of‐sample prediction accuracy.     

THE ROLE OF TRANSACTIONS IN KIND IN DEVELOPING ECONOMIES

The paper is concerned with non-monetized transactions which are dimensionally important in developing countries. The notion of degree of monetization attaches to all real flows. It is necessary to analyze non-monetized transactions in order to a have a better understanding of the producing and consuming activities of households which contribute a large part of national product in less developed countries. Among different non-monetized flows, particular attention is paid to the use of the output of own production for different purposes. A survey of Indian information on the degree of non-monetization shows that it is different for different flows: highest for consumption, intermediate for current inputs and lowest for investments. Cross section Indian data indicate that the degree of non-monetization is expected to fall with the improvement in the average household expenditure and urbanisation but it may rise if development occurs largely through agricultural improvement. Some of the Indian findings may apply to other developing countries as well. Normally, estimates of expenditure elasticities based on cross section data are obtained from consumption expenditure on a particular item (e) and the aggregate consumption expenditure (E) without going into the question of the degree of non-monetization of either element. Since traditional models of consumer behaviour apply only to the relation between money expenditure on a particular item (e_m) and the aggregate money expenditure (E_m), it is suggested that the relation between e and E should be broken down into relations between (i) e_m and E_m, (ii) e_k and E_k where these are the corresponding kind elements and (iii)among E, E_m and E_k. Some estimates of elasticity based on this scheme are presented indicating that the procedure is reasonable and suggesting that this type of analysis would probably furnish a suitable framework for answering relevant questions in the field.     

Relational contracts with subjective peer evaluations

We study optimal dynamic contracting for a firm with multiple workers where compensation is based on public performance signals and privately reported peer evaluations. We show that if evaluation and effort provision are done by different workers (e.g., consider supervisor‐agent hierarchy), first‐best can be achieved even in a static setting. However, if each worker both exerts effort and reports peer evaluations (e.g., consider team setting), effort incentives cannot be decoupled from truth‐telling incentives. This makes the optimal static contract inefficient. Relational contracts based on public signals increase efficiency. Interestingly, the optimal contract may ignore signals that are informative about effort.