Estimating ordered parameters by linear programming

There are many models that require the estimation of a set of ordered parameters. For example, multivariate analysis of variance often is formulated as testing for the equality of the parameters versus an ordered alternative. This problem, referred to as isotonic inference, constrained inference, or isotonic regression, has led to the development of general solutions, not often easy to apply in special models. In this expository paper, we study the special case of a separable convex quadratic programming problem for which the optimality conditions lead to a readily solved linear complementarity problem in the Lagrange multipliers, and subsequently to an equivalent linear programming problem, whose solution can be used to recover the solution of the original isotonic problem. The method can be applied to estimating ordered correlations, ordered binomial probabilities, ordered Poisson parameters, ordered exponential scale parameters, or ordered risk differences.     

RAILROADS AND GROWTH IN PRUSSIA

We study the effect of railroad access on urban population growth. Using GIS techniques, we match triennial population data for roughly 1,000 cities in 19th‐century Prussia to georeferenced maps of the German railroad network. We find positive short‐ and long‐term effects of having a station on urban growth for different periods during 1840–1871. Causal effects of (potentially endogenous) railroad access on city growth are identified using propensity score matching, instrumental variables, and fixed‐effects estimation techniques. Our instrument identifies exogenous variation in railroad access by constructing straight‐line corridors between nodes. Counterfactual models using pre‐railroad growth yield no evidence to support the hypothesis that railroads appeared as a consequence of a previous growth spurt.     

The Holodomor law and national trauma construction in Ukraine

This article proposes to conceptualize the remembrance of the 1932–33 famine, known as the Holodomor, as cultural trauma construction in Ukraine. This entails the study of how the memory of this devastating historical event became the national collective symbol of suffering with which Ukrainians identify today. Based on Jeffrey Alexander’s concept of cultural trauma, the analysis focuses on the role of political elites and their claim-making regarding the meaning of the famine. Focusing specifically on the 2006 Holodomor law as the main claim of the Ukrainian policy-makers, the article investigates their definition of the historical event, their naming of victims and perpetrators, and their social mediation of famine representations. The article reveals how, through their definition of the Holodomor as genocide, the political elites promoted the understanding that Ukrainians experienced the years of 1932–33 differently from other Soviet nations. The Holodomor law should therefore be seen in the context of Ukrainian nation-building policy, which aims to forge a distinct Ukrainian collective identity.     

Exploitation aversion: When financial incentives fail to motivate agents

Studies of the principal-agent relationship find that monetary incentives work in many instances but that they can also backfire. Various mechanisms for this failure have been examined (e.g., intrinsic motivation, image concerns). We posit that an aversion to being exploited, i.e., being used instrumentally for another’s benefit, can also cause incentives to fail. Using an experiment we find that compliance is lower for exploitative principals compared to neutral ones despite using the same contracts. To corroborate our results we show that surveyed “exploitation aversion” mediates this effect. Our results have implications for the design and implementation of incentives within organizations.     

Evaluating the impact of utility company billing plans on residential energy consumption

Many utility companies offer their customers the choice of participation in an average payment plan, which enables them to pay a fixed sum for their utility bill each month (with final settlement at the end of the billing year), instead of the conventional “pay as you go” billing procedure. Because customers on average payment plans are protected from paying large bills during peak energy-use seasons and because the information about monthly energy use and its cost is perhaps less salient to them, it was hypothesized that customers on the average payment plan would use more electricity than customers not on the plan. Using a nonequivalent control group design, the electricity consumption of a selection of customers of two utility companies (Ns = 475 and 74) was examined. The results showed that there was no evidence to support the hypothesis. Since the logic of hypothesis testing does not permit the ready acceptance of the null hypothesis, several procedural, methodological, and statistical points were made to buttress the conclusion that the average payment plans had no effect on electricity consumption.     

The TRIPs agreement and technological innovation

In this paper we attempt to evaluate the possible spill-over of the international agreement on Trade-Related Aspects of Intellectual Property rights (TRIPs for short), underwritten in 1994, regarding economic growth for both wealthy and developing countries. We find that the TRIPs convention has prompted, at the same time, innovation in developing countries and a rise in the per capita income for all the economies involved in international commerce. As a by-product of our research we find that, despite the strong growth of resident patents application after 1995 (the year in which TRIPs came into force), most of the increase in the gross domestic product per capita in developing countries is attributable to the international transfer of technologies, via foreign direct investments.     

The role of reciprocation in social network formation,with an application to LiveJournal

This paper deals with the role of reciprocation in the formation of individuals’ social networks. We follow the activity of a panel of bloggers over more than a year and investigate the extent to which initiating a relation brings about its reciprocation. We adapt a standard capital investment model to study how reciprocation affects the build-up of the individual social capital of bloggers, as measured by their links and interactions with others. This allows us to measure the role of content production and relationship building in the dynamics of online social networks and to distinguish between the social networking and media aspects of blogging.     

Geography, demography, and early development

This paper explores the role of geography in early development. It presents a model where the odds of survival are higher in geographically favorable regions. In such regions, higher life expectancy prompts parents to devote more of their resources to old-age consumption and enables them to invest relatively more in the quantity and quality of their offspring. Investment in education, together with population growth, helps geographically-favorable economies to attain high levels of a more educated population that is necessary for sustained economic growth. The empirical evidence is generally supportive of the view that geographic attributes influenced regional population levels in Europe and its colonial offshoots around 1500 A.D. and that they affected population levels and educational attainment in low-income countries of the 1990s. For useful comments and suggestions I thank the editor, two anonymous referees, Daron Acemoglu, Ann Carlos, Phil Graves, Naci Mocan, Oded Stark, seminar participants at the University of Colorado at Boulder, the University of Colorado at Denver, and the 2002 Royal Economic Society Annual Conference. I owe a special debt of gratitude to my advisor Herschel Grossman who passed away in October 2004 after leaving his mark on many of us in the profession. The standard disclaimer applies. Responsible editor: Alessandro Cigno.     

Dynamic factor models

Summary Factor models can cope with many variables without running into scarce degrees of freedom problems often faced in a regression-based analysis. In this article we review recent work on dynamic factor models that have become popular in macroeconomic policy analysis and forecasting. By means of an empirical application we demonstrate that these models turn out to be usefu in investigating macroeconomic problems.