City Decline in an Urbanizing World - Preliminary - Luis E. Quintero and Paula Restrepo October 23, 2019 Urbanization studies and policy focuses on managing urban growth for the devel- oping world. However, a large portion of the developing world present urban decline. The first contributions of the paper will be to simply present this fact with a large scale dataset that spans more than 2 decades for the Europe and Central Asia region. The economic effect of population decline is quantified through the use of city level Night Lights data. The second contributions if to specify a model that explains deliv- ers predictions and test them. The first prediction, that market access has a negative impact on city performance in a context of population decline is is different from the usual positive effect found in the literature, which focuses on places with growing pop- ulation. Second, the model suggests that productivity will increase after population declines, especially in large cities. The first one is supported by the data, while the second is not, although some endogeneity concerns remain. The tests are performed for 5,548 cities between 1989 and 2013. We take particular notice of factors that are of particular importance to this region, such as the existence of monotowns, in which many countries have faced challenges transitioning from a centrally planned economy to a market-based economy following the collapse of the Soviet Union. Keywords: Migration, Urban Decline, Urban infrastructure, Eastern Europe, Gravity Models. 1 1 Introduction Policy and academic research on city dynamics in the developing world overwhelmingly focuses on the growth of cities in both area and population, as well as in the increasing urbanization of countries Geography(2009); Glaeser and Xiong(2017); Chauvin et al.(2017). Desmet and Henderson(2015) warns against using without caution what we have learned from developed countries to predict what will happen in developing countries, which further motivates our inquiry into this particular world region. City growth and overall urbanization are tightly linked to overall development (Henderson, 2014). The objective and contributions of this paper are threefold. First, it presents evidence on the striking phenomenon of population decline in Eastern Europe and Central Asia (ECA) using a novel dataset that spans more than 3 decades for all cities in the countries of the region. This evidence is aimed at motivating the stylized fact that a large portion of the developing world has entered a demographic transition before attaining the typical develop- ment levels associated with it. Second, it present a simple model (in progress) that provides predictions of the role of market access and other determinants of population redistribution in a context of population decline. The model is based on Brezis and Krugman(1997) model of life cycle of cities. In our case, we do not model a change in technology, but instead a shock to the city population. This model provides two main predictions: first, that in a context when a group of cities face a negative population shock, population is redistributed to places with larger markets; as a consequence, market access acts more as a push than a pull factor, increasing the population movement out of those cities with large market access. Second, that the state of technology and infrastructure is durable. As a consequence, in the short run, when population declines cities increase their productivity. This effect is even stronger in cities with more knowledge and infrastructure, which we proxy with local market size. Third, it tests these predictions. The first one is confirmed. Our estimation finds that mar- ket potential has a negative effect on population growth on cities that are already declining, which supports the model's idea that inhabitants located in a shrinking city j perceive larger markets located closer to them as incentives to migrate out of j and not as potential markets to sell products that would make staying in j more attractive. This is a robust result to different specifications of market potential, inclusion of instrumental variables to control for market potential endogeneity, and different treatments of the error structure in estimation. This new empirical results contrasts with the existing literature (see for example Henderson and Wang(2007)) and provides justification for allowing heterogeneity in the reaction of urban systems to positive and negative shocks. The second result, whether productivity is increased after population decreases, gives us mixed results. The estimation use novel data 2 to measure aggregate proximity to other markets, or market access (including using driving distances instead of geodesic distances between cities to incorporate costs of poor transport infrastructure or hazardous topography), as well as size of local market using night lights (NLs) to measure economic activity. 2 Population Shock in the ECA Region Most countries in Eastern Europe and Central Asia (ECA)1region experienced a negative population shock at the end of the 1980s. The total population of the country either declined or its growth rate was significantly slowed down. Figure 1c shows population growth rates for the world. Since 1990, ECA suffered a strong decline in its population growth rates, reaching absolute population decline in 1998. This region presented growth rates that are lower than those of richer industrialized economies which have gone through a demographic transition2, while having economic development levels of other developing region with much larger growth rates (marker size denotes GDP per capita of the region). Being an already highly urbanized region, the ECA countries have seen their urban system suffer the effects of this negative population shock. 1c shows that many of these countries have experienced a decline in more than 80% of their cities. The average number of cities with absolute population loss in ECA countries whose populations have decelerated are 77% between 1990 and 2000, and 72% between 2001 and 2012, which is dramatic.3 This decline is dramatic. In contrast, for instance, Glaeser and Gyourko(2005) study population decline in US metropolitan areas. They find only 6.72% of the counties considered losing population, with an average loss of 9%. These demographic changes are closely related to widespread structural changes that took place during the transition from centrally planned to market oriented economies, especially the loosening of migration restrictions which increased migration outflows, and the loss of child bearing benefits that incentivized an accelerated decline in fertility.4As discussed, these 1ECA refers to the low and medium income countries as classified by the World Bank (high-income economies, those with a GNI per capita of $12,476 or more are excluded). The countries in this region are: Al- bania, Armenia, Azerbaijan, Belarus, Bosnia and Herzegovina, Bulgaria, Georgia, Kazakhstan, Kosovo, Kyr- gyz Republic, Macedonia, Moldova, Montenegro, Romania, Russian Federation, Serbia, Tajikistan, Turkey, Turkmenistan, Ukraine, and Uzbekistan. Our analysis leaves out Armenia, Azerbaijan, Bosnia and Herze- govina, Kosovo, Macedonia, Montenegro, Turkmenistan due to data availability constraints. 2Myrskyl¨aet al.(2009) review the conclusive body of evidence of a negative correlation between fertility and industrial development, a theory that posits that at high levels of economic development societies undergo a transition led by lower fertility rates that results in lower population growth rates. ECA seems to have gone through such transition without the development levels usually associated with it. 3City population comes from our main dataset, collected from censuses and projections for 5,548 cities in 17 countries. See detail in section5. 4Figure ?? shows net migration and fertility rates for the region, and their decline, which approximately 3 national trends have permeated the urban system. National fertility and migration rates, alone, explain 52 percent of ECA's cities population growth variance (table6). Mobility. Strict mobility restrictions kept the urban systems in an equilibrium that was far from that implied by individual decisiones in a market systems. From Thunen and Hall(1966) and Fujita and Krugman(1995), to the more recent quantitative spatial mod- els surveyed in Redding and Rossi-Hansberg(2017), spatial equilibrium, the methodological workhorse that leads most of our modern understanding of cities, assumes wages, prices, pop- ulation, and the housing stock are endogenous and jointly determined. This determination is driven by agent's making location decisions, both within and across cities, following arbi- trage opportunities that appear as a response to shock, until prices adjust and remove any incentives for moving. During the centrally planned regimes, these price adjustments were not possible, and resources were constantly in a state of suboptimality. Not only was move- ment of workers strictly controlled both across and within countries, trade across locations and the local housing rents were exogenously determined by the central government too. As a consequence, for example, both population and economic activity was more widespread in space than observed in market based economies during the same decades (Markevich and Mikhailova, 2013). Henderson and Wang(2007) found that more than a decade after tran- sition, countries which urbanized under planned economies had significant lower levels of urban concentration