We analyze an economy where firms undertake both innovation and adoption of technologies from the world technology frontier. The selection of high-skill managers and firms is more important for innovation than for adoption. As the economy approaches the frontier, selection becomes more important. Countries at early stages of development pursue an investment-based strategy, which relies on existing firms and managers to maximize investment, but in return, sacrifices selection. Closer to the world technology frontier, economies switch to an innovation-based strategy with short-term relationships, younger firms, less investment and better selection of firms and managers. We show that relatively backward economies may switch out of the investment-based strategy too soon, so certain policies, such as limits on product market competition or investment subsidies, that encourage the investment-based strategy may be beneficial. However, these policies may have significant long-run costs, because they make it more likely that a society will be trapped in the investment-based strategy and fail to converge to the world technology frontier.

This introduction to the plm package is a slightly modified version of Croissant and Millo (2008), published in the Journal of Statistical Software. Panel data econometrics is obviously one of the main fields in the profession, but most of the models used are difficult to estimate with R. plm is a package for R which intends to make the estimation of linear panel models straightforward. plm provides functions to estimate a wide variety of models and to make (robust) inference. Keywords:˜panel data, covariance matrix estimators, generalized method of moments, R. 1.

Abstract. Due partly to costly information, price dispersion across markets is common in developed and developing countries. Between 2001 and 2006, cell phone service was phased in throughout Niger, providing an alternative and cheaper search technology to grain traders and other market actors. We construct a novel theoretical model of sequential search, in which traders engage in optimal search for the maximum sales price, net transport costs. The model predicts that cell phones will increase traders’ reservation sales prices and the number of markets over which they search, leading to a reduction in price dispersion across markets. To test the predictions of the theoretical model, we use a unique market and trader dataset from Niger that combines data on prices, transport costs, rainfall and grain production with cell phone access and trader behavior. We first exploit the quasi-experimental nature of cell phone coverage to estimate the impact of the staggered introduction of information technology on market performance. The results provide evidence that cell phones reduce grain price dispersion across markets by a minimum of 6.4 percent and reduce intra-annual price variation by 10 percent. Cell phones have a greater impact on price dispersion for market pairs that are farther away, and for those with lower road quality. This effect becomes larger as a higher percentage of markets have cell phone coverage. We provide empirical evidence in support of specific mechanisms that partially explain the impact of cell phones on market performance.

This article reassesses the importance of colonial status to investors before 1914 by means of multivariable regression analysis of the data available to contemporaries. We show that British colonies were able to borrow in London at significantly lower rates of interest than noncolonies precisely because of their colonial status, which mattered more than either gold standard adherence or the sustainability of fiscal policies. The “empire effect ” was, on average, a discount of around 100 basis points, rising to around 175 basis points for the underdeveloped African and Asian colonies. Colonial status significantly reduced the default risk perceived by investors. t was obvious to contemporaries—among them John Maynard Keynes—that membership in the British Empire gave poor countries access to the British capital market at lower interest rates than would have been required had they been politically independent. For liberal critics of the empire, this “empire effect ” seemed detrimental to the economic health of the British Isles, which might otherwise have attracted

For 40 years, the gravity equation has been a workhorse for cross-country empirical analyses of international trade flows and – in particular – the effects of free trade agreements (FTAs) on trade flows. However, the gravity equation is subject to the same econometric critique as cross-industry studies of U.S. tariff and nontariff barriers and U.S. multilateral imports: trade policy is not exogenous. The potential endogeneity of FTA binary right-hand-side variables motivates developing a theory of FTA determination compatible with the theory of international trade flows. Allowing econometrically for the potential FTA variable’s endogeneity yields striking empirical results: the effect of FTAs on trade flows is quintupled.

Contract farming is a pervasive institutional arrangement in cash cropping economies in Mozambique. Empirical evidence on its nature and, especially, the extent to which policies can generate broad based income growth and poverty reduction is lacking. This study investigates the rationale for persistence, the determinants of farmer participation and performance in cotton and tobacco schemes (Essay One), and the economy-wide effects of expansion and shocks in cotton and tobacco sectors on poverty reduction in concession areas of the Zambezi valley of Mozambique (Essay Two). In the first essay, we find that in both sectors contract farming is an institutional response to widespread failure in input, credit and output markets and the absence of a functional public and market based service provision network. Two stage econometric procedures (testing for the existence of threshold effects in land holdings and educational attainment) indicate that in both areas participation in the schemes is driven by factor endowments, asset ownership and alternative income opportunities, and very little by demographic factors. Also, there are no returns to education in either sector; this result is consistent with previous research in Mozambique but surprising in an agronomically

This paper studies the role of consumer learning in the demand for recorded music by examining the impact of an artist’s new album on sales of past and future albums. Using detailed album sales data for a sample of 355 artists, we show that the release of a new album increases sales of old albums, and the increase is substantial and permanent—especially if the new release is a hit. Various patterns in the data suggest the source of the spillover is information: a new release causes some uninformed consumers to discover the artist and purchase the artist’s past albums. We develop and estimate a structural learning model that allows us to quantify the impact of consumers ’ lack of information on market outcomes. Our estimates imply that the distribution of sales is substantially more skewed than it would be if consumers were more fully informed, and that sales of non-debut albums are roughly 25 % higher than they would be without the benefit of information generated by previous albums.

This paper unifies three complementary approaches to defining, identifying, and estimating causal effects: the classical structural equations approach of the Cowles Commision; the treatment effects framework of Rubin (1974) and Rosenbaum and Rubin (1983); and the Directed Acyclic Graph (DAG) approach of Pearl. The settable system framework nests these prior approaches, while affording significant improvements to each. For example, the settable system approach permits identification of causal effects without requiring exogenous instruments; instead, a weaker conditional exogeneity condition suffices. It removes the stable unit treatment value assumption of the treatment effect approach and provides significant insight into the selection of covariates. It generalizes the DAG ap-proach by accommodating mutual causality and attributes. We provide a variety of results ensuring structural identification of general covariate-conditioned average causal effects, laying the founda-tion for parametric and nonparametric estimation of effects of interest and new tests for structural identification.

This paper unifies three complementary approaches to defining, identifying, and estimating causal effects: the classical structural equations approach of the Cowles Commision; the treatment effects framework of Rubin (1974) and Rosenbaum and Rubin (1983); and the Directed Acyclic Graph (DAG) approach of Pearl. The settable system framework nests these prior approaches, while affording significant improvements to each. For example, the settable system approach permits identification and estimation of causal effects without requiring exogenous instruments, generalizing the classical structural equations approach; it relaxes the stable unit treatment value assumption of the treatment effect approach and provides significant insight into the selection of covariates; and it accommodates mutual causality, generalizing the DAG approach. We provide necessary and sufficient conditions for identification of covariate-conditioned average causal effects, parametric and nonparametric estimation results, and new tests for unconfoundedness.

The increasing prevalence of HIV in Rwanda, along with the likelihood of continued effects of the genocide of 1994, suggests that many rural households may be facing extreme stress, and their agricultural production may be changing. Policymakers and development practitioners seek to understand how Rwandan households are affected and how they are reacting to the stress so that development policies can best support improvements in rural livelihoods under this changing environment. If production systems are shifting to less nutritious crop mixtures or ones that increase the potential for soil erosion on the hillsides, measures may be needed to counterbalance the negative effects. This research seeks to evaluate the agricultural strategies used by households in dealing with morbidity and mortality and to determine differences in crop production between households that have experienced a recent adult illness or death from illness and those without adult morbidity or mortality. With 90 percent of the population living in rural and semirural settings and engaged in agriculture, the consequences of illness and death may be reflected in agricultural production, particularly