Emergence and Evolution of Heterogeneous Spatial Patterns

We live in a quite heterogeneous space. There are cities and rural areas, and population density varies a lot across space. People migrate and commute to the places of their work. The goal of this article is to clarify the mechanism of commuting as an equilibrium in heterogeneous space with different technologies. It is well known that agricultural production requires substantial amount of land per unit of labour, while most industrial production and services require much lower land input. We assume that all industrial production and service sector is located in urban areas, while all agriculture is in rural area. Historically, the share of labour in agriculture was declining due to more rapid growth of productivity there in comparison to service sector. At the same time, people change the location of their residence much slower. That is why at some point in time we face the situation, when rural area has excessive labour (not enough work for all in agriculture), while urban areas create an increasing number of jobs. A relatively simple mathematical model is proposed to explain the emergence of spatial pattern with heterogeneous density and phase transition between urban and rural areas. There are three types of agents: workers who live in a city, farmers who live in a rural area and workers-commuters from rural area to a city. In an equilibrium they are indifferent between occupation and residence. An indifference across locations for a priori identical agents implies the shape of land rent. If some parameters of the model change, they imply the change of the whole spatial pattern. In particular, split of rural residents into commuters and farmers depends on road infrastructure development through transport cost. Two types of shocks (decline in commuting transport cost by construction of fast roads and the relative decline in agricultural price) can perturb agricultural zone. Some former farmers start commuting to city while keeping residence in rural area. This is how a functional area of a city with integrated labour market emerges.

Water - Spatial Network Pricing

The paper addresses an important issue of pricing mechanisms is spatially distributed systems with losses, with an application to water supply system. When losses from delivery are high, the asymmetry of spatial location of consumers plays an important role, which is captured by the model. The goal is to compare the efficiency from alternative market structures for water supply. The model can be applied for channels aimed on water redistribution. In particular, the model can be relevant for analysing different market structures, equilibrium water pricing and efficiency for the planned channels. Potential application can be planned channel between river Ebro (Spain) and communities Valencia and Murcia. While this paper is purely theoretical, it addresses the issues that are still little understood at administrative level. Water market as described is a necessity, but it will not emerge spontaneously and it requires appropriate legislative preparation. Mathematical model is designed in terms of densities and flows of corresponding economic variables.

Potential and Spatial Structure of Population

The goal of this work is to suggest a mechanism explaining different spatial patterns of residential locations. The basic idea is counterbalance of centripetal and centrifugal forces. This paper complements the previous author's works in this area. This article addresses the following questions: a) agglomeration potential, b) optimal city size, c) equilibrium agricultural density, d) influence of agglomeration on land rent. Both relative location and size distribution of cities and residential patterns in agricultural areas represent interesting objects of study. There exist two main forces, centripetal (agglomeration) and centrifugal (congestion) that shape urban areas. The origin of agglomeration forces is in scale economies, while congestion forces represent a cumulative negative externality from such agglomeration. Following the stylized facts about different production technologies, it is assumed that agricultural technology creates dispersion force (through intensive land use), while industrial technology creates agglomeration force. It is possible to find the optimal city size assuming some scale economies in production counterbalanced by commuting costs. Location heterogeneity is balanced across residents via location rent to bring identical utility. There might be two possibilities: finite optimal size (for low scale economies) and infinitely large city (for high scale economies). The rural community of farmers is also considered. Here the average distance to neighbor (as a proxy to market access) is balanced with the benefits from land ownership. The optimal rural population density is the point maximizing this potential. Finally, the spatial equilibrium is constructed. It consists of discrete cities of optimal size attracting certain fraction of the population and the continuous farmland between them. The concept of potential for agro-industrial cluster is also introduced. It is assumed that rural resident has an access to scale economies in production of a city via commuting, and also has land slot for agricultural activity. There exists equilibrium land rent giving agents identical utility.

A Land Far Away

What goods to export and where to sell them? Our research was pursuing these two major goals. The first one is related to detecting countries where Austria has good perspectives for boosting its export. The basic idea was to use macroeconomic data set detecting the significant variables. We found that besides the GDP of importer and distance, there are more important variables like being landlocked, language, inflation, and so forth. We found recent GDP growth rate to be non-significant in more than just the very basic models. Taking all explanatory variables into account we could calculate the country-effects, telling us how Austrian exporters are under or over-represented within each country. It is argued that exporters could put additional efforts into quickly growing countries where Austria is still under-represented. The second goal was a more detailed view on the role of transport costs. Gravity model was shown to be correct and robust (even for a class of functions of distance). The detailed accounting for transport costs requires consideration of different transport modes and ratios of value to weight. Distance suppresses trade of cheap goods most, suggesting that Austria has no disadvantage in export of high-tech goods (like pharmaceutics and complex machines) over long distances. In particular, pharmaceutical sector has growing potential and trade with Russia is one of its perspectives.International Trade, Gravity Model, Transport Cost, Growth, Advantage

Economic Role of Population Density

The role of population density for economic activity was neglected in most part of economic theory. This paper is a review and extension of the previous works of the author in this field. So far, densities did not become common economic variables in economic analysis, and two countries with different densities of population and infrastructure but similar in macroeconomic parameters are treated as similar. One of the presented models is about an influence of population density on infrastructure development, and later on country potential for economic growth (Yegorov 2005a). Self-organization of production activity in space is elaboration of the ideas of von Thunen. When a city emerges as a center of industrial activity, it deforms the space, and agricultural land rent becomes a function of distance due to transport cost to bring the good to the market. Population density plays an important role in harvesting societies, i.e. those that depend on agriculture and natural resources. Too high population density decreases the natural endowment per capita, but eases the development of infrastructure, leading to existence of an optimal population density for economic growth (Yegorov, 2009). The trade-off between scale economies and transport costs leads to an optimal area served by a local monopolist. In the world with low population density competition might not even emerge because even monopolist can become bankrupt due to low demand density, especially in the environment of high transport costs. Such situation took place on the most part of Russian territory after liberalization that also lead to an increase in relative transport costs. Population density also can play role for an optimal size of a country. While there are many other reasons (mostly historical), spatial structure is also important. Land area of a country is considered as some capital bringing rent from natural resource extraction. The length of a border requires protection efforts and thus is a first type of cost. Commuting with the capital is another type of cost, and here the population density also matters. All these 3 factors enter with different power, and optimization with respect to linear scale give different results (Yegorov, 2005b). Literature 1. Yegorov Y. (2005a) Role of Density and Field in Spatial Economics. ? In: Yee Lawrence (Ed). ?Contemporary Issues in Urban and Regional Economics?. Nova Science Publishers, 2005, N.Y., p.55-78. 2. Yegorov Y. (2005b) Dynamically Sustainable Economic Equilibria as Self-Organized Atomic Structures (2005b) ? In: M.Salzano, A.Kirman, Eds., ?Economics: Complex Windows?, Springer-Verlag Italia, 2005, p.187-199 3. Yegorov Y. (2009) Socio-economic influences of population density. - Chinese Business Review, vol.8, No. 7, p.1-12

Uncertainty of timing for global challenges and problems with transition to renewable energies

What will come first ? non-acceptable global warming or extinction of oil reserves? Both processes can bring substantial costs to the mankind, but their order has important economic implications. The answer to this question will either lower oil price in the long run or will lead to its further rise. It is very important for Russian economy. From the global perspective, both dangers should be taken into account, and transition to renewable energies is the only remedy for both. However, the optimal speed of this transition depends on temporal dynamics of both threats that is highly uncertain at this moment. The goal of this paper is to review the problems with different renewable energies and to outlay different scenarios for the timing of major impact from global warming and oil peak. The problems with renewable energies have mostly economic origin. The global resources of hydropower are limited. While wind is already cheap, it should be balanced due to stochastic supply. Solar energy also needs to be balanced and is still relatively expensive. Oil products and their liquid renewable substitutes (biofuels) will thus remain an important compliment to electricity in the long run. However, biofuels are competing with agriculture for land, and thus can replace only a limited fraction of energy. The first signs of global warming bring the costs today and it comes as increased frequency of extreme weather phenomena (hurricanes, floods, etc). The rate of temperature increase has some range of uncertainty but it generally accepted that +2 degrees is an acceptable limit, and it might come in the middle of the 21st century. One of the policies to deal with it is not to extract all fossil fuels from the ground. However, it is highly likely that all oil will be extracted before global warming will have severe consequences. Since only biofuels can substitute oil in transport, given the current trend in transportation, peak oil can cause too much demand for biofuels, that will be dangerous for food security. Both the price of oil and biofuels would rise to such level, that current level of transportation will be impossible. This can cause resettlement of people to smaller cities. It is possible to conclude that while renewable energies represent a remedy, full transition will not be easy

Emergence and Evolution of Heterogeneous Spatial Patterns

We live in a quite heterogeneous space. There are cities and rural areas, and population density varies a lot across space. People migrate and commute to the places of their work. The goal of this article is to clarify the mechanism of commuting as an equilibrium in heterogeneous space with different technologies. It is well known that agricultural production requires substantial amount of land per unit of labour, while most industrial production and services require much lower land input. We assume that all industrial production and service sector is located in urban areas, while all agriculture is in rural area. Historically, the share of labour in agriculture was declining due to more rapid growth of productivity there in comparison to service sector. At the same time, people change the location of their residence much slower. That is why at some point in time we face the situation, when rural area has excessive labour (not enough work for all in agriculture), while urban areas create an increasing number of jobs. A relatively simple mathematical model is proposed to explain the emergence of spatial pattern with heterogeneous density and phase transition between urban and rural areas. There are three types of agents: workers who live in a city, farmers who live in a rural area and workers-commuters from rural area to a city. In an equilibrium they are indifferent between occupation and residence. An indifference across locations for a priori identical agents implies the shape of land rent. If some parameters of the model change, they imply the change of the whole spatial pattern. In particular, split of rural residents into commuters and farmers depends on road infrastructure development through transport cost. Two types of shocks (decline in commuting transport cost by construction of fast roads and the relative decline in agricultural price) can perturb agricultural zone. Some former farmers start commuting to city while keeping residence in rural area. This is how a functional area of a city with integrated labour market emerges

Market Structure and Sustainable Use of Natural Resources

Sustainable use of natural resources becomes an important issue today not only due to global warming and pollution issues but also because of critical pressure on the Earth?s regeneration possibility. We cannot use classical microeconomic approach here for two reasons: a) impossibility to create natural resources, both exhaustible and renewable, by simple use of labour and capital (like it is done on most of macroeconomic growth models); b) important role of spatial distribution and transport cost than leads to both overharvesting and under-harvesting in some regions. Due to these externalities market organization is extremely important for sustainability, and this question will be studied here in theoretical framework. The goal of this paper is to study the role of market structure for the sustainable harvesting of natural resources. This work is theoretical and uses explicit spatial structure as a component of production function. It continues other works of Yegorov (2005, 2007, 2009) where economic production function accounted explicitly for topological properties of geographical space. Contrary to the previous works, this uses also reproduction equation for renewable resources. The intensity of harvesting follows from market structure and is driven not only by population density but also by land ownership, land rent, transport cost and discount for future. The results show that overharvesting can originate in purely market laws because it does not account for an interaction between economy and nature. The models show that optimal harvesting of natural resources is highly sensitive to such economic parameters as the price of final good, energy price index, land rent and time discount. Land ownership by small farmers keeps the hope of more sustainable resource exploitation because they do not care about land rent and virtually have no time discount. However, they can also overexploit the resource if they have no idea about its dynamics under harvesting. Super-rational farmers who have such knowledge can choose lower land slots and exploit them moderately. However, they can loose competition to farmers who are rational only in economic sense and overexploit their land slots. References 1. Yegorov Y. (2005) Role of Density and Field in Spatial Economics? ? In: Yee Lawrence (Ed). Contemporary Issues in Urban and Regional Economics. Nova Science Publishers, 2005, N.Y., p.55-78. 2. Yegorov Y. (2007) Dynamics of Spatial Infrastructure with Application to Gas and Forest, 6th Conference on Applied Infrastructure Research (Infraday), TU Berlin, Germany, 5-6 October 2007. 3. Yegorov Y. (2009) Socio-economic influences of population density. Chinese Business Review, vol.8, No. 7, p.1-12

Population Structures in Russia: Optimality and Dependence on Parameters of Global Evolution

The paper is devoted to analytical investigation of the division of geographical space into urban and rural areas with application to Russia. Yegorov (2005, 2006, 2009) has suggested the role of population density on economics. A city has an attractive potential based on scale economies. The optimal city size depends on the balance between its attractive potential and the cost of living that can be proxied by equilibrium land rent and commuting cost. For moderate scale effects optimal population of a city depends negatively on transport costs that are related positively with energy price index. The optimal agricultural density of population can also be constructed. The larger is a land slot per peasant, the higher will be the output from one unit of his labour force applied to this slot. But at the same time, larger farm size results in increase of energy costs, related to land development, collecting the crop and bringing it to the market. In the last 10 years we have observed substantial rise of both food and energy prices at the world stock markets. However, the income of farmers did not grow as fast as food price index. This can shift optimal rural population density to lower level, causing migration to cities (and we observe this tendency globally). Any change in those prices results in suboptimality of existing spatial structures. If changes are slow, the optimal infrastructure can be adjusted by simple migration. If the shocks are high, adaptation may be impossible and shock will persist. This took place in early 1990es in the former USSR, where after transition to world price for oil in domestic markets existing spatial infrastructure became suboptimal and resulted in persistent crisis, leading to deterioration of both industry and agriculture. Russia is the largest country but this is also its problem. Having large resource endowment per capita, it is problematic to build sufficient infrastructure. Russia has too low population density and rural density declines further due to low fertility and migration to cities. Those factors limited the growth of the USSR, but after the economic reforms of 1990s the existing infrastructure became exposed to permanent shock of high transport costs. Due to large distances it is optimal to return to gasoline and thus transport subsidy. This will work also against disintegration of the country

Water - Spatial Network Pricing

The paper addresses an important issue of pricing mechanisms is spatially distributed systems with losses, with an application to water supply system. When losses from delivery are high, the asymmetry of spatial location of consumers plays an important role, which is captured by the model. The goal is to compare the efficiency from alternative market structures for water supply. The model can be applied for channels aimed on water redistribution. In particular, the model can be relevant for analysing different market structures, equilibrium water pricing and efficiency for the planned channels. Potential application can be planned channel between river Ebro (Spain) and communities Valencia and Murcia. While this paper is purely theoretical, it addresses the issues that are still little understood at administrative level. Water market as described is a necessity, but it will not emerge spontaneously and it requires appropriate legislative preparation. Mathematical model is designed in terms of densities and flows of corresponding economic variables