The spatial dynamics of new firm births during an economic crisis: the case of Great Britain, 2004–2012

Abstract

Spatial variations in entrepreneurial activity have been shown to be a time persistent phenomenon in many countries. This paper analyses how these spatial variations have been affected by the recent financial crisis within the context of theories of regional resilience and adaptability. The analysis applies Exploratory Spatial Data Analysis techniques to data on firm births across Local Authority Districts of Great Britain during the period 2004–2012. The results demonstrate that, whilst the overall shape of the spatial distribution of firm births remained persistent, there is evidence of an increase in regional inequality. This is primarily associated with a divergence between London and the rest of the distribution. London, together with part of its surrounding area, appears to constitute a resilient entrepreneurial regime that has generated a dynamic, adaptive response to the crisis with high rates of new firm formation in contrast to other regions which have remained locked into lower rates of entrepreneurship. This supports the view that regional entrepreneurship is a path dependent process: entrepreneurial regions are more adaptable to the effects of an exogenous shock than less entrepreneurial regions. Accordingly, entrepreneurship is a critical factor influencing the resilience of regions in responding to an economic crisis.     

Stochastic leader–follower DEA models for two-stage systems

Data envelopment analysis (DEA) is a non-parametric approach for measuring the relative efficiencies of peer decision making units (DMUs). In recent years, it has been widely used to evaluate two-stage systems under different organization mechanisms. This study modifies the conventional leader–follower DEA models for two-stage systems by considering the uncertainty of data. The dual deterministic linear models are first constructed from the stochastic CCR models under the assumption that all components of inputs, outputs, and intermediate products are related only with some basic stochastic factors, which follow continuous and symmetric distributions with nonnegative compact supports. The stochastic leader–follower DEA models are then developed for measuring the efficiencies of the two stages. The stochastic efficiency of the whole system can be uniquely decomposed into the product of the efficiencies of the two stages. Relationships between stochastic efficiencies from stochastic CCR and stochastic leader–follower DEA models are also discussed. An example of the commercial banks in China is considered using the proposed models under different risk levels.     

A network approach for assembling and linking input–output models

Input–output (IO) models, describing trade between different sectors and regions, are widely used to study the environmental repercussions of human activities. A frequent challenge in assembling an IO model or linking several such models is the absence of flow data with the same level of detail for all components. Such problems can be addressed using proportional allocation, which is a form of algebraic transformations. In this paper, we propose a novel approach whereby the IO system is viewed as a network, the topology of which is transformed with the addition of virtual nodes so that available empirical flow data can be mapped directly to existing links, with no additional estimation required, and no impact on results. As IO systems become increasingly disaggregated, and coupled to adjacent databases and models, the adaptability of IO frameworks becomes increasingly important. We show that topological transformations also offer large advantages in terms of transparency, modularity and increasingly importantly for global IO models, efficiency. We illustrate the results in the context of trade linking, multi-scale integration and other applications.     

An economic–probabilistic model for risk analysis in technological innovation projects

This paper presents the application of an economic–probabilistic model to conduct risk analysis in technological innovation (TI) projects. The model integrates risk and economic analysis by quantifying both value and probability of occurrence of cash flow deviations, thus resulting in an economic–probabilistic analysis of the expected returns. The main risk categories and factors in TI projects are identified and associated to cash flow groups. The model allows to calculate risk-adjusted values for cash flow groups and project net present value through stochastic simulation. As a result, the model provides both the risk-adjusted project economic return with the associated probability distribution to its NPV and the variability that each risk factor generates in the project return. The model offers important benefits from the point of view of practitioners, including a condensed list of independent risk factors and the use of a monetary scale to assess risk impact which is familiar to most decision makers.     

A necessary and sufficient condition for the positivity of the growth rate in the Neumann–Gale model of economic growth

In the paper I will discuss an extension of the classical problem of the positivity of the growth rate in the Gale–Neumann model. I will show that the exploitation of the labour is a necessary and sufficient condition for the positivity of the growth rate.     

How economic globalization affects urban expansion: an empirical analysis of 30 Chinese provinces for 2000–2010

Quality & Quantity - Using the globalization theory as the base, this study draws on cross-provincial panel data from 2000 to 2010 to analyze the effect of globalization on China’s urban...     

Statistical evaluation of Data Envelopment Analysis versus COLS Cobb–Douglas benchmarking models for the 2011 Brazilian tariff revision

In 2011, the Brazilian Electricity Regulator (ANEEL) implemented a benchmarking model to evaluate the operational efficiency of power distribution utilities. The model is based on two benchmarking methods: Data Envelopment Analysis (DEA) and Corrected Ordinary Least Squares (COLS) with a Cobb Douglas production function. Although the estimated scores are highly correlated, differences between the scores are as high as 41%. For some companies differences between the efficiency scores result in substantial reduction in regulatory operational costs. We provide a detailed statistical comparison which indicates that the COLS Cobb Douglas model has major deficiencies in terms of estimating efficiency scores.     

Second-best cost–benefit analysis in monopolistic competition models of urban agglomeration

This paper examines the agglomeration benefits of a transportation improvement in a city by modeling the microstructure of urban agglomeration based on monopolistic competition of differentiated intermediate products. Properly extended to include variety distortion in addition to price distortion, Harberger’s measure of excess burden yields the agglomeration benefits. The agglomeration benefits are positive if increasing the variety is procompetitive; however, in the anticompetitive case, we cannot exclude the possibility of negative additional benefits. If there are multiple cities, the net agglomeration benefits can be negative when other cities that experience a reduction in population have larger agglomeration economies.     

Forecasting performances of three automated modelling techniques during the economic crisis 2007–2009

In this work we consider the forecasting of macroeconomic variables during an economic crisis. The focus is on a specific class of models, the so-called single hidden-layer feed-forward autoregressive neural network models. What makes these models interesting in the present context is the fact that they form a class of universal approximators and may be expected to work well during exceptional periods such as major economic crises. Neural network models are often difficult to estimate, and we follow the idea of White (2006) of transforming the specification and nonlinear estimation problem into a linear model selection and estimation problem. To this end, we employ three automatic modelling devices. One of them is White’s QuickNet, but we also consider Autometrics, which is well known to time series econometricians, and the Marginal Bridge Estimator, which is better known to statisticians. The performances of these three model selectors are compared by looking at the accuracy of the forecasts of the estimated neural network models. We apply the neural network model and the three modelling techniques to monthly industrial production and unemployment series from the G7 countries and the four Scandinavian ones, and focus on forecasting during the economic crisis 2007–2009. The forecast accuracy is measured using the root mean square forecast error. Hypothesis testing is also used to compare the performances of the different techniques.     

The impact of the economic cycle on fatal injuries. The case of UK 1971–2007

The aim of this paper is to investigate the effect of the economic cycle on workplace accidents. In particular, the effect of the usual factors of the economic cycle (GDP per capita, Unemployment) is examined along with the effect of working hours (to account for flexible employment) on fatal injuries (to exclude the effect of under-reporting data) for the period 1971?C2007 in UK. Detailed multiple regression analysis is applied, which indicates a controversial and inelastic relation of GDP per capita (negative) and unemployment rate (positive), but also an elastic relation of working hours (positive) to fatal injuries. Further research in data of various countries is proposed before arriving to certain conclusions.     

How to design virus containment policies? A joint analysis of economic and epidemic dynamics under the COVID-19 pandemic

Journal of Economic Interaction and Coordination - We analyze the impact of different designs of COVID-19-related lockdown policies on economic loss and mortality using a micro-level simulation...     

Managing partner opportunism in public–private partnerships: the dynamics of governance adaptation

ABSTRACT

Controlling partner opportunism in public–private partnership (PPP) is still controversial despite its extensive adoption. We demonstrate that partner opportunism gets controlled by the extent to which deployed governance mechanisms are aligned with the governance needs of the transaction. As unique constraint, the institutional voids limit this alignment. If not aligned with governance needs, governance adaptation cycle continues, resulting in extensive or minimally acceptable partner opportunism. The organizations tolerate opportunism as long as they derive some economic value. In the context of institutional voids, the risk of exploitation of incomplete contracts is high but if governed effectively PPPs could still deliver value.     

Higher education and economic growth: A longitudinal study of European regions 2000–2017

This paper investigates the impact of regional higher education systems (HESs) on economic growth, based upon 284 European regions (NUTS 2) over an 18-year period (from 2000 to 2017). The empirical framework specifically models the heterogeneity of the HESs by including indicators on university concentration, on the size of the HES and on HES performance and other important factors. The analysis is based on a novel and integrated dataset, created by collecting and combining indicators from different data sources (Eurostat, OECD, WHED and InCites). The results reveal that an increase in number of universities in a region is conducive to stronger economic growth within that region. The quality of research and a specialisation in STEM subjects are the primary drivers through which universities impact positively on the regions’ economic development.     

Contribution of female human capital in economic growth: an empirical analysis of Pakistan (1972–2012)

This study is to find out an impact of female human capital on economic growth of Pakistan. The study has therefore, used gender separate human capital as an explanatory variable along with other factors, labor force and physical capital. In this regard a composite human capital has been constructed by taking education and health as a proxy for human capital. The long run and short run dynamics among female human capital and economic growth are empirically tested on time series data spread from 1972–2012. Johanson’s co-integration approach has been applied for the long run and Vector Error Correction Model used for the short run relationship. The results show that the long run relationship between female human capital and economic growth is positive and significant. While the short run impact of female human capital on economic growth is positive but statistically insignificant.     

Disequilibrium models of single family housing prices and transactions: The case of Chicago, 1972–1976

This paper reports a first application of Fair-Jaffee type short-side models of disequilibrium to the intraurban single family housing market in which the housing stock is divided into distinct geographic community areas. Data on single family dwelling transactions and prices in the city of Chicago between 1972–1976 is used to estimate four versions of the Fair-Jaffee type model. The approach allows the simultaneous estimation of the price elasticity of the demand for and offer of existing single family dwellings. The demand elasticity estimate of about −0.5 agrees with other estimates in the literature obtained from equilibrium models. The price elasticity of offer has not been previously estimated for single family dwellings. It is found to be around 2.1. Elasticities are also computed with respect to the mortgage interest rate and the intensity of transactions in the dwelling's community area. The disequilibrium models appear substantially superior to equilibrium specifications. Simulations with the estimated models predict that, in the absence of external shocks, transaction prices and quantities stabilize within 2 years.     

Easy come,easy go: Short-term land-use dynamics vis à vis regional economic downturns

The present study postulates distinctive land-use dynamics along the economic cycle, and tests against diverging trends over time of urban and non-urban land-uses with characteristic economic potential. Short-term land-use changes over seven time windows encompassing the last three decades (1992–2020) were investigated in metropolitan Athens (Greece), a mono-centric region experiencing complex economic downturns. Based on diachronic land-use maps with homogeneous spatial resolution and nomenclature derived from ESA Climate Change Initiative (ESA-CCI), a change detection analysis was run considering mean patch size, distance from downtown, and specific entropy-based metrics of landscape diversification (Shannon-Wiener H’ diversity index and Pielou J evenness index). Results of a canonical correlation analysis document differential intensity and spatial direction of change during expansions and recessions associated with distinctive socio-demographic profiles. Metropolitan growth followed a radio-centric (land-saving) model during economic expansions with intense urbanization of fringe land. A more dispersed settlement model – reflecting urban sprawl – was associated with economic stagnations, involving land at progressively distant locations from downtown. Landscape diversification was higher under stagnations and lower during expansions.     

Self-employment and business cycle persistence: Does the composition of employment matter for economic recoveries?

Self-employment comprises an important share of employment in many countries, and tends to expand during downturns through higher inflows from unemployment. Furthermore, countries with higher self-employment shares exhibit lower cyclical output persistence. I build a business cycle model with frictional labor markets where individuals can be self-employed or salaried employed. I show that economies with larger self-employment shares exhibit faster economic recoveries. Differences in the ease of entry into self-employment as the economy recovers explain the contrasting cyclical dynamics. The model successfully captures the cyclical patterns of self-employment and the relationship between self-employment and output persistence in the data.     

Wage inequality and the labor market impact of economic transformation: Croatia, 1970–2008

In this paper, we examine wage inequality and wage differentials in Croatia from 1970 to 2008 using two long aggregate time series on the distribution of income. We focus especially on changing income inequality related to educational and vocational attainment, changing income inequality within those groups, and how these two components of inequality were affected by the economic transformation from socialism to capitalism. We find that income inequality between groups rose moderately post-transformation, while overall inequality increased more sharply. This finding is consistent with a growing importance of individual rather than group productivity in labor market compensation, a change broadly consistent with the economic transformation of the Croatian labor market.