Built environment analysis for road traffic hotspot locations in Moshi,Tanzania

Road traffic injuries (RTIs) cause significant morbidity and mortality in low- and middle-income countries. Investigation of high risk areas for RTIs is needed to guide improvements. This study provides built environmental analysis of road traffic crash hotspots within Moshi, Tanzania. Spatial analysis of police data identified 36 hotspots. Qualitative comparative analysis revealed 40% of crash sites were on local roads without night lighting and increased motorcycle density. Paved narrow roads represented 26% of hotspots and 13% were unpaved roads with uneven roadsides. Roadside unevenness was more predominate in low risk [n = 19, (90.5%)] than high risk sites [n = 7 (46.7%)]. Both low [n = 6 (28.6%)] and high risk [n = 1 (6.7%)] sites had minimal signage. All sites had informal pedestrian pathways. Little variability between risk sites suggests hazardous conditions are widespread. Findings suggest improvement in municipal infrastructure, signage and enforcement is needed to reduce RTI burden.     

The dynamics of the growth of firms: evidence from the services sector

Using a dynamic panel data model with serial correlation in the error term, the purpose of this paper is to examine if Gibrat’s Law can be rejected for the services sector as it has been for manufacturing. The aim of this paper is also to improve the understanding of the empirical determinants of firm growth by extending the literature to include a new variable related to foreign participation. In addition, and based on recent developments in the growth of firms, our analysis also includes the role of the financial structure. The sample used is an unbalanced panel data set that includes all size classes, including the smallest surviving firms, from the Portuguese service sector over the period from 1995 to 2001. Applying the GMM-system estimator our findings suggest that Gibrat’s Law is rejected for the services firms. In addition, the results also indicate that firm growth is mainly explained by firm size and age. These results have significant policy implications.

Planning for Agricultural Change and Economic Transformation in Tanzania?

Recently, Tanzania witnessed a revival of economic planning that explicitly aimed to combine rapid economic growth with accelerated structural transformation of the economy. To achieve these planning targets would require a relatively modest drop in the share of agriculture in GDP, but a dramatic fall in its share in employment by 2025. Tanzanian planners assume that labour is locked in agriculture because agricultural productivity is low, from which they conclude that, to release labour to fuel the expansion of manufacturing, it is imperative to raise agricultural productivity by appropriate land policies, leveraging private investment and developing public–private partnerships. We argue that, analytically, this planning argument leaves out the possibility that causality may run the other way – from high labour retention in agriculture to low agricultural productivity – and that, empirically, the observed patterns inherent in actual processes of economic transformation in Tanzania do not tally well with the assumptions of planners. More specifically, in so far as labour flows out of agriculture, it flows towards informal‐sector activities, both rural and urban, rather than towards formal manufacturing.     

Firm growth and R&D: Evidence from the Portuguese manufacturing industry

This work studies the effects of R&D activities and investment, both physical and R&D, on the growth of firms by considering a dynamic firm growth model with serial correlation. The main hypotheses maintain that firms with a strong commitment to R&D have a higher growth rate, and investment has a positive effect on firm growth. We investigate such relations with reference to an unbalanced panel data set of Portuguese manufacturing firms over the period of 1990 to 2001. We find that a systematic tendency for smaller firms to grow more quickly is the main reason why firm growth is not entirely stochastic.     

Firm Growth and Liquidity Constraints: A Dynamic Analysis

Using a large unbalanced panel data set of Portuguese manufacturing firms surviving over the period from 1990 to 2001, the purpose of this paper is to examine whether liquidity constraints faced by business firms affect firm growth. We use a GMM-system to estimate a dynamic panel data model of firm growth that incorporates cash flow as a measure of liquidity constraints and persistence of growth. The model is estimated for all size classes, including micro firms. Our findings reveal that smaller and younger firms have higher growth-cash flow sensitivities than larger and more mature firms. This is consistent with the suggestion that financial constraints on firm growth may be relatively more severe for small and young firms. Nevertheless, the same finding can be interpreted in a different way if we consider the more recent literature which interpret the higher investment/cash flow sensitivity of younger and smaller firm in absence of financial market imperfection as the outcome of these firms reaction to the fact that realisation of their cash flows reveals them the direction to go in presence of uncertainty of their growth prospect. Besides, firms that were small and young at the beginning of the sample period exhibited more persistent growth than those that were large and old. Finally, these results have significant policy implications.      

Testing Gibrat’s Law: Empirical Evidence from a Panel of Portuguese Manufacturing Firms

The purpose of this paper is to use Dynamic Panel Data (DPD) models with serial correlation in the error term to see if Gibrat’s law holds and to analyse the empirical determinants of firm growth. This paper makes significant contributions to the empirical literature on the dynamics of firm growth, since it updates the work carried out by previous researchers in this field using micro panel data, dynamic firm growth models with serial correlation in the error term, panel unit root tests and GMM‐system estimator. To conduct this study we used an unbalanced panel of Portuguese manufacturing firms over the period from 1990 to 2001. The main implication of our findings is that firm growth is not quite random since there are some determinants which exert influence on firm growth.