Many models of growth and development assume that aggregate output is generated by a Cobb Douglas specification for the aggregate production function with labor, physical capital, and sometimes human capital as inputs. In this paper we question the empirical relevance of the Cobb Douglas specification. We consider new World Bank data on GDP, the labor supply, the stock of physical capital and educational attainment per worker for a panel of 82 countries over a 28 year period fi'om 196(b87. These data are used to estimate a general CES production function specification for which the Cobb Douglas specification is a special case. We find that for the entire 82 country 28 year panel we can reject a Cobb Douglas specification for the aggregate production function. When we divide our sample of 82 countries up into several subsamples based on initial levels of capital per worker, we find that we can continue to reject a Cobb Douglas specification. In particular, we find that physical capital and human capital adjusted labor are more substitutable in the richest group of countries and less substitutable in the poorest group of countries than would be implied by a Cobb Douglas specification. We discuss the implications of our findings for the debate concerning convergence in income levels across countries as well as for the plausibility of long run endogenous growth due to the specification of the production technology.

We empirically examine the role of social networks in welfare participation using data on language spoken at home to better infer networks within an area. Our empirical strategy asks whether being surrounded by others who speak the same language increases welfare use more for those from high welfare-using language groups. This methodology allows us to include local area and language group �xed effects and to control for the direct effect of being surrounded by one’s language group; these controls eliminate many of the problems in previous studies. The results strongly con�rm the importance of networks in welfare participation. I.

An innovative business practice attributed to the information technology industry is the aggressive use of employee stock options to compensate executives and other employees. The pervasiveness of stock options among high-tech firms in Silicon Valley is often described as a phenomenon unique to the Valley’s culture. In this study, we investigate whether the greater use of stock options in the information technology industry can be explained on the basis of general economic relationships that apply to firms in all industries. Our empirical model is a system of simultaneous equations that captures the interconnectedness between compensation, performance, and specific forms of compensation. We document the impact of the form of compensation on performance and total compensation. Based on previous literature, we also identify economic factors expected to influence the use of stock options and show that there are significant differences between information technology and other industries. While these factors explain much of the greater use of options in the information technology firms, a significant residual difference remains. Considering these factors, we also find that executives in the information technology industry are not compensated at a level higher than those in other industries.

The existence of an empirical relationship between the adoption of an IMF programme and the concession of a debt rescheduling by commercial and ocial creditors is tested using a bivariate probit model. If countries who have arrangements with the IMF are more likely than others to obtain a rescheduling of their external debt we could conclude that the adoption of an IMF programme could work as a sort of signal of a country's "good willingness", which is thus rewarded with the debt relief. The results confirm the existence of a significant effect of the adoption of an IMF programme on the subsequent concession of a debt rescheduling by creditors.

A firm's ability to compete in new product markets is vital to its profitability and long-term survival. Therefore, it is important to understand the development and growth of these markets. Following a pioneering study by Bass (1969), diffiusion models have traditionally provided this understanding in marketing. The great appeal of the Bass model is that it is a simple one that fits the data very well and provides parameters that have an intuitive behavioural interpretation. The model suffers from three wellknown limitations: (1) it does not include marketing variables that could influence new product diffusion and sales; (2) the model's parameters are unstable; and (3) the model's forecasts are inaccurate before the sales peak and especially prior to the point of inflection. Subsequent research has made progress especially in extending the Bass model to include marketing variables. However, the extensions have come at the cost of simplicity: the new models are far more complex than the simple Bass model. We propose an alternate simple model of new product growth for consumer durables, based on the concept of affordability rather than on diffusion. We compare this model with the diffusion model in terms of fit, stability and validity of parameters, and forecasting ability. The alternate model is a little inferior to the diffusion model in fit, but superior in terms of the stability and validity of parameters and forecasting ability. We discuss the limitations and implications of our model.

We analyzed the consumer’s payment option to use debit, general purpose credit cards, gasoline credit cards, or cash. Based on the results from a nested multinomial logit model, we found consumers are more likely to use cash when they have less education, lower incomes, are middle-aged, and own fewer credit cards. Debit and credit card users are younger, more educated, and hold more credit cards. Respondents who use their debit card are less likely to use their gasoline credit card. The results suggest that greater debit card usage will place the greatest competitive pressure on the gasoline credit card

Drawing on an in-depth governance micro-survey of public officials within a country, we address empirically the question of the relative importance of the various determinants of governance. We investigate the causes of poor governance, and show that commonly made inferences about policy based on simple correlation can be highly misleading, because the high correlation between the various governance (and public sector management) determinants, as well as the endogeneity in these variables. We find that undue emphasis may have been given in previous work to a number of conventional public sector management variables (such as civil servant wages, internal enforcement of rules, autonomy of agency by fiat, etc.), while undermining the priority due to more ‘external ’ (to public sector management) variables, such as external voice, transparency, and politicization. The latter set of ‘voice’-related variables has larger affect on the quality of service and corruption than the more traditional public sector management type of variables. Further work drawing in depth on country-specific surveys in other settings is warranted to ascertain with more confidence whether a shift towards more prominence to transparency and ‘voice’-type of variables is needed, backstopping the results for Bolivia in this paper.

Stochastic programming is a powerful modelling paradigm for asset and liability management problems. It incorporates in a common framework multiple correlated sources of risk for both the asset and liability side, takes a long time horizon perspective, accommodates different levels of risk aversion and allows for dynamic portfolio rebalancing while satisfying operational or regulatory restrictions and policy requirements. This chapter introduces stochastic programming models for broad classes of asset and liability management problems, describes procedures for generating the requisite event trees, discusses the validity of model results for illustrative applications, compares stochastic programming with alternative modelling approaches, and hinges upon solution techniques and computational issues.

In this paper, we consider a form of multi-issue negotiation where a shop negotiates both the contents and the price of bundles of goods with his customers. We present some key insights about, as well as a procedure for, locating mutually beneficial alternatives to the bundle currently under negotiation. The essence of our approach lies in combining aggregate (anonymous) knowledge of customer preferences with current data about the ongoing negotiation process. The developed procedure either works with already obtained aggregate knowledge or, in the absence of such knowledge, learns the relevant information online. We conduct computer experiments with simulated customers that have nonlinear preferences. We show how, for various types of customers, with distinct negotiation heuristics, our procedure (with and without the necessary aggregate knowledge) increases the speed with which deals are reached, as well as the number and the Pareto efficiency of the deals reached compared to a benchmark.

Designing efficient bidding strategies for sequential auctions represents an important, open problem area in agent-mediated electronic markets. In existing literature, a variety of bidding strategies have been proposed and have been shown to perform with varying degrees of efficiency. However, most of strategies proposed so far do not explicitly model bidders attitudes towards risk which, in mainstream economic literature, is considered an essential attribute in modeling agent preferences and decision making under uncertainty. This paper studies the effect that risk profiles (modeled through the standard Arrow-Pratt risk aversion measure), have on the bidders strategies in sequential auctions. First, the sequential decision process involved in bidding is modeled as a Markov Decision Process. Then, the effect that a bidders risk aversion has on her decision theoretic optimal bidding policy is analyzed, for a category of expectations of future price distributions. This analysis is performed separately for the case of first price and second-price sequential auctions. Next, the bidding strategies developed above are simulated, in order to study the effect that an agents risk aversion has on the chances of winning a set of complementary-valued items. The paper concludes with an experimental study of how the presence of risk-averse bidders affects both bidder profits and auctioneer revenue, for different market scenarios of increasing complexity. 1