Former Soviet Union

Statistical Annex

Former Soviet Union     

Labor supply flexibility and portfolio choice in a life cycle model

This paper examines the effect of the labor-leisure choice on portfolio and consumption decisions over an individual's life cycle. The model incorporates the fact that individuals may have considerable flexibility in varying their work effort (including their choice of when to retire). Given this flexibility, the individual simultaneously determines optimal levels of current consumption, labor effort, and an optimal financial investment strategy at each point in his life cycle. We show that labor and investment choices are intimately related. The ability to vary labor supply ex post induces the individual to assume greater risks in his investment portfolio ex ante.     

The sharpest tool in the shed: IPO financial statement management of STEM vs. non-STEM firms

The valuation of STEM (science, technology, engineering, and math) firms has recently gained attention in the literature. Research has shown that, for valuation of STEM firms, accounting items such as sales growth and R&D expenditures matter more than bottom-line earnings. We examine whether, around the time of the IPO, STEM managers apply discretion over the accounting items most weighted by investors for their valuation. We find that investors tend to weigh sales growth and R&D more heavily than earnings in valuing STEM firms and that managers respond by managing those items rather than bottom-line earnings as in prior research. We find that future stock returns of STEM firms are negatively associated with sales management and not with abnormal accruals as for non-STEM firms. Our results illuminate the differential behavior of STEM managers and highlight the importance of a departure from the traditional IPO earnings management paradigm, which assumes that firms mainly manage their earnings.     

Ethical and Fair Work Behaviour: A Normative-Empirical Dialogue Concerning Ethics and Justice

Towards the general goal of generating a normative-empirical dialogue about ethics and justice, the present study explored three issues: (1) the extent to which the normative criteria of ethics and justice prescribed by moral philosophers are indeed reflected in managerial professionals' subjective beliefs of what ethical and just work behaviour ought to be, (2) the relationship between people's ought beliefs and their perceptions of actual ethical and just work behaviour, and (3) the relationship between the notions of ethics and justice. To do so, a review of the normative and positive theories of ethics was carried out which revealed the key normative criteria of ethics (i.e., utility, rights, justice, principle and care) and justice (i.e., due procedure and due outcome). Using both the interview and the repertory grid procedures, key determinants of ethical and just work behaviour as perceived by the managerial professionals were generated. These determinants were used to construct the questionnaires for the assessment of people's subjective ought beliefs, and their is judgements, of ethical and just work behaviour. There were three respondent samples: managerial professionals, general public and university students. Results showed that (1) people's subjective ought beliefs closely reflected the normative standards of ethics and justice, (2) there were significant discrepancies between people's subjective ought beliefs and their perceptions of actual ethical and just work behaviour, (3) individual differences in ought beliefs had some influence on is judgements, (4) both the ought beliefs and is judgements pertaining to the notion of justice could be accounted for by measures of the other four criteria of ethics and in particular, the notion of rights. The implications of the findings for normative theories of ethics and for ethics education are discussed.     

Empirical Patterns of Firm Growth and R&D Investment: a Quality Ladder Model Interpretation

We present a partial equilibrium model of endogenous firm growth with R&D investment and stochastic innovation as the engines of growth, drawing on the quality ladder models in the macro growth literature, and the literature on patent races and the discrete choice models of product differentiation. The model fits a number of empirical patterns well, including: (i) a skewed size distribution of firms with persistent differences in firm sizes, (ii) firm growth independent of firm size, as stated in the so-called Gibrat's law, and (iii) R&D investment proportional to sales.     

Rank-dependent preferences without ranking axioms

A key feature of the rank-dependent model for decision making under risk is that the weighting of an outcome depends on its relative rank. This theory received numerous axiomatizations, however, all these sets of axioms need to make an explicit reference to the ranking of the outcomes. This situation is unsatisfactory, as it seems to be desirable to get the ranking property of this model as a consequence of the model, rather than as an assumption. [Yaari, M.E., 1987. The dual theory of choice under risk. Econometrica 55, 95–115] offered a special version of this model (called dual theory), where the utility function is linear. This paper offers a set of axioms implying Yaari’s dual theory without making any reference to the order of the outcomes. The main axiom is called semi betweenness, which, unlike the usual case, is made on random variables rather than on distribution functions.     

The inconsistency of common scale estimators when output prices are unobserved and endogenous

This paper explores the inconsistency of common scale estimators when output is proxied by deflated sales, based on a common output deflator across firms. The problem arises when firms operate in an imperfectly competitive environment and prices differ between them. In particular, we show that this problem reveals itself as a downward bias in the scale estimates obtained from production function regressions, under a variety of assumptions about the pattern of technology, demand and factor price shocks. The result also holds for scale estimates obtained from cost functions. The analysis is carried one step further by adding a model of product demand. Within this augmented model we examine the probability limit of the scale estimate obtained from an ordinary production function regression. This analysis reveals that the OLS estimate will be biased towards a value below one, and how this bias is affected by the magnitude of the parameters and the amount of variation in the various shocks. We have included an empirical section which illustrates the issues. The empirical analysis presents a tentative approach to solve the problem discussed in the theoretical part of this paper.