First Nature vs. Second Nature Causes: Industry Location and Growth in the Presence of an Open-Access Renewable Resource

In this paper we present a model integrating characteristics of the New Economic Geography, the theory of endogenous growth and the economy of natural resources. This theoretical framework enables us to study explicitly the effect of “first nature causes” in the concentration of economic activity, more specifically, the consequences of an asymmetrical distribution of natural resources. The natural resource we consider appears as a localized input in one of the two countries, giving firms located in that country a cost advantage. In this context, after a decrease in transport costs, firms decide to move to the country with the greatest domestic demand and market size, where they can take more advantage of increasing returns, despite the cost advantage of locating in the South, due to the presence of the natural resource.industrial location; endogenous growth; renewable resource; geography

Growth in a Cross-Section of Cities: Location, Increasing Returns or Random Growth?

This article analyzes empirically the main existing theories on income and population city growth: increasing returns to scale, locational fundamentals and random growth. To do this we implement a threshold nonlinearity test that extends standard linear growth regression models to a dataset on urban, climatological and macroeconomic variables on 1,175 U.S. cities. Our analysis reveals the existence of increasing returns when per-capita income levels are beyond $19; 264. Despite this, income growth is mostly explained by social and locational fundamentals. Population growth also exhibits two distinct equilibria determined by a threshold value of 116,300 inhabitants beyond which city population grows at a higher rate. Income and population growth do not go hand in hand, implying an optimal level of population beyond which income growth stagnates or deterioratesthreshold nonlinearity test, locational fundamentals, multiple equilibria, random growth

Growth in a cross-section of cities: location, increasing returns or random growth?

This article analyzes empirically the main existing theories on income and population city growth: increasing returns to scale, locational fundamentals and random growth. To do this we implement a threshold nonlinearity test that extends standard linear growth regression models to a dataset on urban, climatological and macroeconomic variables on 1,175 U.S. cities. Our analysis reveals the existence of increasing returns when per-capita income levels are beyond $19; 264. Despite this, income growth is mostly explained by social and locational fundamentals. Population growth also exhibits two distinct equilibria determined by a threshold value of 116,300 inhabitants beyond which city population grows at a higher rate. Income and population growth do not go hand in hand, implying an optimal level of population beyond which income growth stagnates or deteriorates.Threshold nonlinearity test, locational fundamentals, multiple equilibria, random growth

Trade liberalisation and global-scale forest transition

In this paper, we develop a new theoretical model that explains the forest transition not at a local, but at a worldwide level, in a trade liberalisation scenario. Our model has economic geography foundations: transport costs affect the distribution of firms between countries. We also introduce a renewable natural resource used as an input by manufacturing firms. The results reproduce forest transition behaviour but at a global scale: a decrease in transport costs has a negative effect on the worldwide stock of the natural resource in the short-term, but in the long-term this initial effect is reversed as a consequence of industrial reorganisation between countries because of the change in transport costs.Forest transition; renewable resources; industrial location; geography; trade

Historical urban growth in Europe (1300–1800)

This paper analyses the evolution of the European urban system from a long-term perspective (from 1300 to 1800) considering the historical data set of Bairoch et al. (1988). Using the method recently proposed by Clauset et al. (2009), a Pareto-type city size distribution (power law) is rejected from 1300 to 1600. A power law is a plausible model for the city size distribution only in 1700 and 1800, although the log-normal distribution is another plausible alternative model that we cannot reject. Moreover, random growth of cities is rejected using parametric and non-parametric methods. The results reveal a clear pattern of convergent growth in all periods

Cross-sectional growth in US cities from 1990 to 2000

This paper analyses the growth of American cities, understood as the growth of the population or of the per capita income, from 1990 to 2000. This empirical analysis uses data from all the cities (incorporated places) with more than 25,000 inhabitants in the year 2000 (1152 cities). The results show that while common convergence behaviour is observed in both population and per capita income growth, there are differences in the evolution of the distributions: the population distribution remains almost unchanged, while the per capita income distribution makes a great movement to the right. We use two different methodologies to test cross-sectional convergence across cities: linear growth models (allowing for spatial spillovers between locations) and spatial quantile regressions. We find evidence of significant spatial effects and non-linear behaviour

House Prices and Marriage in Spain

The aim of this study is to examine the link between house prices and marriage in Spain. We consider data from 50 Spanish provinces (NUTS III regions) and from local civil registries in 282 cities with populations greater than 25, 000 inhabitants. The regional data cover the 1995–2018 period, whereas the local sample includes information from 2005 to 2018. The marriage rate is defined as the annual absolute number of marriages per thousand inhabitants in each region or city. We used data on Spain because the Spanish housing market experienced a strong rise in house prices until 2006, when the housing bubble ended and prices dramatically decreased. By using different econometric techniques (panel data models with fixed effects and dynamic panel data models), our results reveal that there is a significant negative relationship between house prices and the marriage rate at both the regional and local levels. Overall, this study highlights the important consequences of rising house prices on family formations. Therefore, public authorities should try to reduce fluctuations in house prices and to facilitate access to home ownership for young couples. © 2022 by the author. Licensee MDPI, Basel, Switzerland

A time series analysis of judicial foreclosures in Spain

There was an unprecedented wave of foreclosures and evictions in Spain after the 2008 global financial crisis. The subsequent Great Recession had strong economic, social and environmental consequences. This paper explores the frequency of permanent shocks in foreclosure quarterly rates (defined as the number of judicial foreclosures per 1000 inhabitants) for 50 Spanish provinces (NUTS 3 regions) during the period from 2001 (Q1) to 2019 (Q4) using time series analysis. We examine whether the foreclosure rate is a stationary series, exhibits a unit root or is stationary around a process subject to structural breaks. A clear finding from this analysis is that not all shocks have transitory effects on the foreclosure rate. The percentage of unit root rejections is around 40%, thus, providing the evidence of both stationarity around occasional shocks that have permanent effects, and of a unit root, where all shocks have a permanent effect on the foreclosure rate. We also test for unit roots allowing for the presence of one and two structural breaks. Most of the structural breaks are positive, and the majority are grouped from 2008 onwards, coinciding with the financial crisis and the subsequent collapse of the Spanish housing bubble. We also find a later decrease in foreclosures in some regions that can be related to the effectiveness of the Code of Good Practice for banks and financial institutions approved in 2012. Nevertheless, the level of the foreclosure rate time series has not returned to the pre-2008 level in any case

The probability distribution of worldwide forest areas

This paper analyses the probability distribution of worldwide forest areas. We find moderate support for a Pareto-type distribution (power law) using FAO data from 1990 to 2015. Power laws are common features of many complex systems in nature. A power law is a plausible model for the world probability distribution of forest areas in all examined years, although the log-normal distribution is a plausible alternative model that cannot be rejected. The random growth of forest areas could generate a power law or log-normal distribution. We study the change in forest coverage using parametric and non-parametric methods. We identified a slight convergence of forest areas over the time reviewed; however, random forest area growth cannot be rejected for most of the distribution of forest areas. Therefore, our results give support to theoretical models of stochastic forest growth

Regional unemployment, marriage, and divorce

In this paper, we examine whether the business cycle plays a role in marriage and divorce. We use data on Spain, since the differences between recession and expansion periods across regions are quite pronounced in that country. We find that the unemployment rate is negatively associated with the marriage rate, pointing to a pro-cyclical evolution of marriage; however the response of the divorce rate to the business cycle is mixed. Results show the existence of different patterns, depending on geography: divorce rates in coastal regions are procyclical, while in inland regions divorces react to unemployment in a counter-cyclical way. Other factors, such as changes in divorce law and duration of the marriage also have a significant effect on divorce rates