Doctor of Philosophy / Department of Agricultural Economics / Michael R. Langemeier / This study applies recent advances in nonparametric techniques to investigate growth in labor productivity and convergence in the Kansas farm sector for a panel of 564 farms for the period 1993-2007. The study seeks to answer two questions: First, what are the sources of labor productivity growth in the farm sector and second, is there evidence of convergence or divergence in the growth rate of labor productivity across farms? Following Kumar and Russell (2002), the nonparametric production frontier approach is used to decompose the growth in output per worker into three components: efficiency change, technical change, and capital deepening. Kernel density estimation methods are used to investigate the evolution of the entire distribution of labor productivity and the effects of each of those three growth components on the evolution of the distributions over the sample periods, 1993-07, 1993-02, and 1996-05. Cross-sectional regression methods (ordinary least square, partial linear model, and smooth coefficient model) are later employed to test for convergence in labor productivity growth and the contribution of each of the components to the convergence process. The study yields the following results. First, capital deepening and technical change are the main sources of labor productivity growth. Efficiency change is a source of regress in productivity growth. Second, technical change is not neutral. Third, the distribution of labor productivity in the farm sector has remained unimodal. Capital deepening and technical change are the main factors contributing to labor productivity distributions. Fourth, despite no evidence of technological catching-up, efficiency change and capital deepening contributed to convergence in the growth rate of labor productivity during the entire sample period. Technical change contributes to productivity disparity in the 1993-07 period. The contribution of technical change in the 1993-02 and 1996-05 periods are mixed with evidence of both convergence and disparity. Finally, the results for the 1993-07 period support the existence of a positive relationship between the annual growth in technical change and initial level of capital-labor ratio, suggesting that technology is embodied in capital accumulation.

This paper suggests an empirical framework for analysing income distribution dynamics and cross-region convergence in the European Union of 27 member states, 1995- 2003. The framework lies in the research tradition that allows the state income space to be continuous, puts emphasis on both shape and intra-distribution dynamics and uses stochastic kernels for studying transition dynamics and implied long-run behaviour. In this paper stochastic kernels are described by conditional density functions, estimated by a product kernel estimator of conditional density and represented by means of novel visualisation tools. The technique of spatial filtering is used to account for spatial effects, in order to avoid misguided inferences and interpretations caused by the presence of spatial autocorrelation in the income distributions. The results reveal a slow catching-up of the poorest regions and a process of polarisation, with a small group of very rich regions shifting away from the rest of the cross-section. This is well evidenced by both, the unfiltered and the filtered ergodic density view. Differences exist in detail, and these emphasise the importance to properly deal with the spatial autocorrelation problem. (authors' abstract)

abstract: In the study of regional economic growth and convergence, the distribution dynamics approach which interrogates the evolution of the cross-sectional distribution as a whole and is concerned with both the external and internal dynamics of the distribution has received wide usage. However, many methodological issues remain to be resolved before valid inferences and conclusions can be drawn from empirical research. Among them, spatial effects including spatial heterogeneity and spatial dependence invalidate the assumption of independent and identical distributions underlying the conventional maximum likelihood techniques while the availability of small samples in regional settings questions the usage of the asymptotic properties. This dissertation is comprised of three papers targeted at addressing these two issues. The first paper investigates whether the conventional regional income mobility estimators are still suitable in the presence of spatial dependence and/or a small sample. It is approached through a series of Monte Carlo experiments which require the proposal of a novel data generating process (DGP) capable of generating spatially dependent time series. The second paper moves to the statistical tests for detecting specific forms of spatial (spatiotemporal) effects in the discrete Markov chain model, investigating their robustness to the alternative spatial effect, sensitivity to discretization granularity, and properties in small sample settings. The third paper proposes discrete kernel estimators with cross-validated bandwidths as an alternative to maximum likelihood estimators in small sample settings. It is demonstrated that the performance of discrete kernel estimators offers improvement when the sample size is small. Taken together, the three papers constitute an endeavor to relax the restrictive assumptions of spatial independence and spatial homogeneity, as well as demonstrating the difference between the small sample and asymptotic properties for conventionally adopted maximum likelihood estimators towards a more valid inferential framework for the distribution dynamics approach to the study of regional economic growth and convergence. / Dissertation/Thesis / Doctoral Dissertation Geography 2018

Organising is the general process by which we structure our world. It is a process that goes beyond social ordering by involving also the technical and the natural realms. Further, it is a process which involves us all. All the time. This dissertation focuses on the organising of business enterprise, more specifically, the organising of food distribution. It is study of formative events in the history of ICA, a major Swedish food distributor. The study provides a detailed account of the development of Hakonbolaget, one of four purchasing centres that formed ICA. Primarily, it accounts for Hakonbolaget´s efforts to establish a modern, rational food distribution system in the 1940s and 1950s. The thrust of these efforts was directed toward three areas of rationalisation: internal operations at the wholesale warehouses, retail operations, and wholesale-retail interaction. Incidentally, these were also central themes in the public debate about the growing costs of goods distribution in Sweden at the time. Through its efforts, Hakonbolaget realised a number of new solutions and established something of a model for modern food distribution. A model that came to characterise operation within ICA from the 1960s and well into the 1990s. Drawing on work within the sociology of science and technology, a conceptual vocabulary is developed for analysing the process of organising. This vocabulary suggests that organising can be regarded as a framing process – as attempts to define and realise sociotechnical situations. The inherent instability of such situations makes stability rather than change a puzzling observation. Consequently, change processes should be regarded as efforts to stabilise situations. Such efforts are closely linked to the establishment of metrics and the generation of representations. In addition to traditional social aspects of organising, the vocabulary also directs attention to the whole heterogeneous materials that surround us. / Diss. Stockholm : Handelshögsk., 2001