New Economic Geography, Empirics, and Regional Policy

There are doubts about the effectiveness of regional policy. Well known are the vain attempts of Italy to bridge the gap between the Mezzogiorno and the North, of Germany to bridge the gap between the Neue Länder and the West, and of the European Commission to reduce regional disparities in general. We validate a salient explanation for the lack of effectiveness: agglomeration advantages lock business activity in relatively prosperous core regions, even though wages and production costs tend to be higher there. On the basis of the `New Economic Geography' - a set of general equilibrium models that focus on location choice - in combination with descriptive statistics and econometric analysis, we conclude that the European economic geography is characterized by a network of local and stable core-periphery systems. Since regional policy tend to be insufficient to counter centripetal market forces, disparities between cores and their peripheries at a subprovincial level of regional aggregation are with us to stay. Moreover, if regional policy does have an impact, it may be adverse as some policies targeted on peripheral regions trigger location choices in favour of core regions.

New economic geography, empirics, and regional policy

There are doubts about the effectiveness of regional policy. Well known are the fruitless attempts of Italy to bridge the gap between the Mezzogiorno and the North, of Germany to bridge the gap between the Neue Länder and the West, and of the European Commission to reduce regional disparities in general. We validate one explanation: agglomeration advantages lock business activity in relatively prosperous core regions, even though wages – and thus production costs – tend to be higher there. We set off from the ‘New Economic Geography’, a set of general equilibrium models that focus on location choice. Theory, descriptive statistics, and econometric analysis support the conclusion that the European economic geography is characterized by a network of local and stable core periphery systems. This implies that disparities between core regions and their peripheries at a (sub) provincial level of regional aggregation are with us to stay, as regional policy targeted on peripheries tends to be insufficient to counter centripetal market forces. Moreover, even if such policy has an impact, it may be adverse, as core regions may benefit disproportionately in the long run. A focus of regional policy on local agglomerations, which have a realistic chance to hold on to economic activity, is therefore desirable.

Competition Among Spatially Differentiated Firms: An Empirical Model with an Application to Cement

The theoretical literature of industrial organization shows that the distances between consumers and firms have first-order implications for competitive outcomes whenever transportation costs are large. To assess these effects empirically, we develop a structural model of competition among spatially differentiated firms and introduce a GMM estimator that recovers the structural parameters with only regional-level data. We apply the model and estimator to the portland cement industry. The estimation fits, both in-sample and out-of-sample, demonstrate that the framework explains well the salient features of competition. We estimate transportation costs to be $0.30 per tonne-mile, given diesel prices at the 2000 level, and show that these costs constrain shipping distances and provide firms with localized market power. To demonstrate policy-relevance, we conduct counter-factual simulations that quantify competitive harm from a hypothetical merger. We are able to map the distribution of harm over geographic space and identify the divestiture that best mitigates harm.

A propos Brexit: on the breaking up of integration areas – an NEG analysis

Inspired by Brexit, the paper explores the effects of splitting an integration area or "Union" on trade Patterns and the spatial distribution of industry. A linear three-region New Economic Geography (NEG) model is developed and two possible situations before separation are considered: agglomeration and dispersion. By analogy with the Brexit options, soft and hard separation scenarios are considered. Firms in the leaving region may move to the larger Union market, even on the periphery, relocation substituting trade; or firms in the Union may move in the more isolated leaving region, escaping from competition. The paper also analyses deeper Union integration following separation. Instances of multistability and complex Dynamics are found

Spatial Relocation with Heterogeneous Firms and Heterogeneous Sectors

The present paper focuses on sorting as a mechanism behind the well-established fact that there is a central region productivity premium. Using a model of heterogeneous firms that can move between regions, Baldwin and Okubo (2006) show how more productive firms sort themselves to the large core region. We extend this model by introducing different capital intensities among firms and sectors. In accordance with empirical evidence, more productive firms are assumed to be more capital intensive. As a result, our model can produce sorting to the large regions from both ends of the productivity distribution. Firms with high capital intensity and high productivity as well as firms with very low productivity and low capital intensity tend to relocate to the core. We use region and sector productivity distributions from Japanese micro data to test the predictions of the model. Several sectors show patterns consistent with two-sided sorting, and roughly an equal number of sectors seem to primarily be driven by sorting and selection. We also find supportive evidence for our model prediction that two-sided sorting occurs in sectors with a high capital intensity.Agglomeration; firm heterogeneity; productivity; spatial sorting

Using the past to constrain the future: how the palaeorecord can improve estimates of global warming

Climate sensitivity is defined as the change in global mean equilibrium temperature after a doubling of atmospheric CO2 concentration and provides a simple measure of global warming. An early estimate of climate sensitivity, 1.5-4.5{\deg}C, has changed little subsequently, including the latest assessment by the Intergovernmental Panel on Climate Change. The persistence of such large uncertainties in this simple measure casts doubt on our understanding of the mechanisms of climate change and our ability to predict the response of the climate system to future perturbations. This has motivated continued attempts to constrain the range with climate data, alone or in conjunction with models. The majority of studies use data from the instrumental period (post-1850) but recent work has made use of information about the large climate changes experienced in the geological past. In this review, we first outline approaches that estimate climate sensitivity using instrumental climate observations and then summarise attempts to use the record of climate change on geological timescales. We examine the limitations of these studies and suggest ways in which the power of the palaeoclimate record could be better used to reduce uncertainties in our predictions of climate sensitivity.Comment: The final, definitive version of this paper has been published in Progress in Physical Geography, 31(5), 2007 by SAGE Publications Ltd, All rights reserved. \c{opyright} 2007 Edwards, Crucifix and Harriso

City Size Distributions As A Consequence of the Growth Process

The size distribution of cities in many countries follows some broadly regular patterns. Any good theory of city size distributions should (i) be able to account for this regularity, but also (ii) rely on a plausible economic mechanism and (iii) be consistent with other fundamental features of cities like the existence of agglomeration economies and crowding costs. Unlike the previous literature, the model proposed here satisfies these three requirements. It views small innovation-driven techno logical shocks as the main engine behind the growth and decline of cities. Cities grow or decline as they win or lose industries following new innovations. Formally, this is achieved by embedding the quality-ladder model of growth developed by Grossman and Helpman in an urban framework.City size distribution, quality-ladder models of growth, agglomeration economies

The impacts of aerosol emissions on historical climate in ukesm1

As one of the main drivers for climate change, it is important to understand changes in anthropogenic aerosol emissions and evaluate the climate impact. Anthropogenic aerosols have affected global climate while exerting a much larger influence on regional climate by their short lifetime and heterogeneous spatial distribution. In this study, the effective radiative forcing (ERF), which has been accepted as a useful index for quantifying the effect of climate forcing, was evaluated to understand the effects of aerosol on regional climate over a historical period (1850–2014). Eastern United States (EUS), Western European Union (WEU), and Eastern Central China (ECC), are regions that predominantly emit anthropogenic aerosols and were analyzed using Coupled Model Intercomparison Project 6 (CMIP6) simulations implemented within the framework of the Aerosol Chemistry Model Intercomparison Project (AerChemMIP) in the UK’s Earth System Model (UKESM1). In EUS and WEU, where industrialization occurred relatively earlier, the negative ERF seems to have been recovering in recent decades based on the decreasing trend of aerosol emissions. Conversely, the radiative cooling in ECC seems to be strengthened as aerosol emission continuously increases. These aerosol ERFs have been largely attributed to atmospheric rapid adjustments, driven mainly by aerosol-cloud interactions rather than direct effects of aerosol such as scattering and absorption.</jats:p

Empiricism and stochastics in cellular automaton modeling of urban land use dynamics

An increasing number of models for predicting land use change in regions of rapidurbanization are being proposed and built using ideas from cellular automata (CA)theory. Calibrating such models to real situations is highly problematic and to date,serious attention has not been focused on the estimation problem. In this paper, wepropose a structure for simulating urban change based on estimating land usetransitions using elementary probabilistic methods which draw their inspiration fromBayes' theory and the related ?weights of evidence? approach. These land use changeprobabilities drive a CA model ? DINAMICA ? conceived at the Center for RemoteSensing of the Federal University of Minas Gerais (CSR-UFMG). This is based on aneight cell Moore neighborhood approach implemented through empirical land useallocation algorithms. The model framework has been applied to a medium-size townin the west of São Paulo State, Bauru. We show how various socio-economic andinfrastructural factors can be combined using the weights of evidence approach whichenables us to predict the probability of changes between land use types in differentcells of the system. Different predictions for the town during the period 1979-1988were generated, and statistical validation was then conducted using a multipleresolution fitting procedure. These modeling experiments support the essential logicof adopting Bayesian empirical methods which synthesize various information aboutspatial infrastructure as the driver of urban land use change. This indicates therelevance of the approach for generating forecasts of growth for Brazilian citiesparticularly and for world-wide cities in general