A multi-field bio-economic model of irrigated grain-cotton farming systems.

We present a participatory modelling framework that integrates information from interviews and discussions with farmers and consultants, with dynamic bio-economic models to answer complex questions on the allocation of limited resources at the farm business level. Interviews and discussions with farmers were used to: describe the farm business; identify relevant research questions; identify potential solutions; and discuss and learn from the whole-farm simulations. The simulations are done using a whole-farm, multi-field configuration of APSIM (APSFarm). APSFarm results were validated against farmers' experience. Once the model was accepted by the participating farmers as a fair representation of their farm business, the model was used to explore changes in the tactical or strategic management of the farm and results were then discussed to identify feasible options for improvement. Here we describe the modelling framework and present an example of the application of integrative whole farm system tools to answer relevant questions from an irrigated farm business case study near Dalby (151.27E - 27.17S), Queensland, Australia. Results indicated that even though cotton crops generates more farm income per hectare a more diversified rotation with less cotton would be relatively more profitable, with no increase in risk, as a more cotton dominated traditional rotation. Results are discussed in terms of the benefits and constraints from developing and applying more integrative approaches to represent farm businesses and their management in participatory research projects with the aim of designing more profitable and sustainable irrigated farming systems.

A dynamic programming model for optimising feeding and slaughter decisions regarding fattening pigs

Costs of purchasing new piglets and of feeding them until slaughter are the main variable expenditures in pig fattening. They both depend on slaughter intensity, the nature of feeding patterns and the technological constraints of pig fattening, such as genotype. Therefore, it is of interest to examine the effect of production technology and changes in input and output prices on feeding and slaughter decisions. This study examines the problem by using a dynamic programming model that links genetic characteristics of a pig to feeding decisions and the timing of slaughter and takes into account how these jointly affect the quality-adjusted value of a carcass. The model simulates the growth mechanism of a pig under optional feeding and slaughter patterns and then solves the optimal feeding and slaughter decisions recursively. The state of nature and the genotype of a pig are known in the analysis. The main contribution of this study is the dynamic approach that explicitly takes into account carcass quality while simultaneously optimising feeding and slaughter decisions. The method maximises the internal rate of return to the capacity unit. Hence, the results can have vital impact on competitiveness of pig production, which is known to be quite capital-intensive. The results suggest that producer can significantly benefit from improvements in the pig's genotype, because they improve efficiency of pig production. The annual benefits from obtaining pigs of improved genotype can be more than €20 per capacity unit. The annual net benefits of animal breeding to pig farms can also be considerable. Animals of improved genotype can reach optimal slaughter maturity quicker and produce leaner meat than animals of poor genotype. In order to fully utilise the benefits of animal breeding, the producer must adjust feeding and slaughter patterns on the basis of genotype. The results suggest that the producer can benefit from flexible feeding technology. The flexible feeding technology segregates pigs into groups according to their weight, carcass leanness, genotype and sex and thereafter optimises feeding and slaughter decisions separately for these groups. Typically, such a technology provides incentives to feed piglets with protein-rich feed such that the genetic potential to produce leaner meat is fully utilised. When the pig approaches slaughter maturity, the share of protein-rich feed in the diet gradually decreases and the amount of energy-rich feed increases. Generally, the optimal slaughter weight is within the weight range that pays the highest price per kilogram of pig meat. The optimal feeding pattern and the optimal timing of slaughter depend on price ratios. Particularly, an increase in the price of pig meat provides incentives to increase the growth rates up to the pig's biological maximum by increasing the amount of energy in the feed. Price changes and changes in slaughter premium can also have large income effects. Key words: barley, carcass composition, dynamic programming, feeding, genotypes, lean, pig fattening, precision agriculture, productivity, slaughter weight, soybeans

Essays on Illegal Activities, Institutions and Economic Growth

In public economics, two extremist views on the functions of a government compete: one emphasizes government working for the public interest to provide value for the citizens, while another regards government mainly as a workhorse for private interests. Moreover, as the sole legitimate authority, the government has the right to define the rules and laws as well as to enforce them. With respect to regulation, two extremes arise: from too little regulation to too much of it. If the government does not function or ceases to exist, the state falls into anarchy or chaos (Somalia). If it regulates too much, it will completely suffocate private activities, which might be considered extralegal (the former Soviet Union). In this thesis I scrutinize the government s interventionist policies and evaluate the question of how to best promote economic well-being. The first two essays assume that the government s policies promote illegal activity. The first paper evaluates the interaction between the government and the mafia, and pays attention to the law enforcement of underground production. We show that the revenue-maximizing government will always monitor the shadow economy, as monitoring contributes to the government s revenue. In general, both legal and illegal firms are hurt by the entry of the mafia. It is, however, plausible that legal firms might benefit by the entry of the mafia if it competes with the government. The second paper tackles the issue of the measurement of the size of the shadow economy. To formulate policies it is essential to know what drives illegal economic activity; is it the tax burden, excess regulation, corruption or a weak legal environment? In this paper we propose an additional explanation for tax evasion and shadow production, namely cultural factors as manifested by religion as determinants of tax morality. According to our findings, Catholic and Protestant countries do not differ in their tax morale. The third paper contributes to the literature discussing the role of the government in promoting economic and productivity growth. Our main result is that, given the complex relationship between economic growth and economic freedom, marketization has not necessarily been beneficial in terms of growth. The last paper builds on traditional growth literature and revisits the debate on convergence clubs arising from demographic transition. We provide new evidence against the idea that countries within a club would converge over time. Instead, we propose that since the demographic transition is a dynamic process, one can expect countries to enter the last regime of stable, modern growth in stages.

Dynamic Factor Models and Forecasting Finnish Macroeconomic Variables

In recent years, thanks to developments in information technology, large-dimensional datasets have been increasingly available. Researchers now have access to thousands of economic series and the information contained in them can be used to create accurate forecasts and to test economic theories. To exploit this large amount of information, researchers and policymakers need an appropriate econometric model.Usual time series models, vector autoregression for example, cannot incorporate more than a few variables. There are two ways to solve this problem: use variable selection procedures or gather the information contained in the series to create an index model. This thesis focuses on one of the most widespread index model, the dynamic factor model (the theory behind this model, based on previous literature, is the core of the first part of this study), and its use in forecasting Finnish macroeconomic indicators (which is the focus of the second part of the thesis). In particular, I forecast economic activity indicators (e.g. GDP) and price indicators (e.g. consumer price index), from 3 large Finnish datasets. The first dataset contains a large series of aggregated data obtained from the Statistics Finland database. The second dataset is composed by economic indicators from Bank of Finland. The last dataset is formed by disaggregated data from Statistic Finland, which I call micro dataset. The forecasts are computed following a two steps procedure: in the first step I estimate a set of common factors from the original dataset. The second step consists in formulating forecasting equations including the factors extracted previously. The predictions are evaluated using relative mean squared forecast error, where the benchmark model is a univariate autoregressive model. The results are dataset-dependent. The forecasts based on factor models are very accurate for the first dataset (the Statistics Finland one), while they are considerably worse for the Bank of Finland dataset. The forecasts derived from the micro dataset are still good, but less accurate than the ones obtained in the first case. This work leads to multiple research developments. The results here obtained can be replicated for longer datasets. The non-aggregated data can be represented in an even more disaggregated form (firm level). Finally, the use of the micro data, one of the major contributions of this thesis, can be useful in the imputation of missing values and the creation of flash estimates of macroeconomic indicator (nowcasting).

Lessons from the northern hake long-term management plan: Could the economic assessment have accepted it?

An economic expert working group (STECF/SGBRE-07-05) was convened in 2007 for evaluating the potential economic consequences of a Long-Term Management Plan for the northern hake. Analyzing all the scenarios proposed by biological assessment, they found that keeping the F in the status quo level was the best policy in terms of net present values for both yield and profits. This result is counter intuitive because it may indicate that effort costs do no affect the economic reference points. However, it is well accepted that the inclusion of costs affects negatively the economic reference points. In this paper, applying a dynamic agestructured model to the northern hake, we show that the optimal fishing mortality that maximizes the net present value of profits is lower than Fmax.

Dynamic Inefficiency in an Overlapping Generation Economy with Pollution and Health Costs

Revised 2008-08.-- Published as an article in: Journal of Public Economic Theory (2008), 10(4), 563-594.

The Evaluation of Fisheries Management: A Dynamic Stochastic Approach

In this article, we analyze how to evaluate fishery resource management under “ecological uncertainty”. In this context, an efficient policy consists of applying a different exploitation rule depending on the state of the resource and we could say that the stock is always in transition, jumping from one steady state to another. First, we propose a method for calibrating the growth path of the resource such that observed dynamics of resource and captures are matched. Second, we apply the calibration procedure proposed in two different fishing grounds: the European Anchovy (Division VIII) and the Southern Stock of Hake. Our results show that the role played by uncertainty is essential for the conclusions. For European Anchovy fishery (Division VIII) we find, in contrast with Del Valle et al. (2001), that this is not an overexploited fishing ground. However, we show that the Southern Stock of Hake is in a dangerous situation. In both cases our results are in accordance with ICES advice.

Coastal erosion as a natural resource management problem: An economic perspective

Unremitting waves and occasional storms bring dynamic forces to bear on the coast. Sediment flux results in various patterns of erosion and accretion, with an overwhelming majority (80 to 90 percent) of coastline in the eastern U.S. exhibiting net erosion in recent decades. Climate change threatens to increase the intensity of storms and raise sea level 18 to 59 centimeters over the next century. Following a lengthy tradition of economic models for natural resource management, this paper provides a dynamic optimization model for managing coastal erosion and explores the types of data necessary to employ the model for normative policy analysis. The model conceptualizes benefits of beach and dune sediments as service flows accruing to nearby residential property owners, local businesses, recreational beach users, and perhaps others. Benefits can also include improvements in habitat for beach- and dune-dependent plant and animal species. The costs of maintaining beach sediment in the presence of coastal erosion include expenditures on dredging, pumping, and placing sand on the beach to maintain width and height. Other costs can include negative impacts on the nearshore environment. Employing these constructs, an optimal control model is specified that provides a framework for identifying the conditions under which beach replenishment enhances economic welfare and an optimal schedule for replenishment can be derived under a constant sea level and erosion rate (short term) as well as an increasing sea level and erosion rate (long term). Under some simplifying assumptions, the conceptual framework can examine the time horizon of management responses under sea level rise, identifying the timing of shift to passive management (shoreline retreat) and exploring factors that influence this potential shift. (PDF contains 4 pages)

Resource management of dynamic coastal environments using synoptic measures from remote sensing

In addition to providing vital ecological services, coastal areas of North Carolina provide prized areas for habitation, recreation, and commercial fisheries. However, from a management perspective, the coasts of North Carolina are highly variable and complex. In-water constituents such as nutrients, suspended sediments, and chlorophyll a concentration can vary significantly over a broad spectrum of time and space scales. Rapid growth and land-use change continue to exert pressure on coastal lands. Coastal environments are also very vulnerable to short-term (e.g., hurricanes) and long-term (e.g., sea-level rise) natural changes that can result in significant loss of life, economic loss, or changes in coastal ecosystem functioning. Hence, the dynamic nature, effects of human-induced change over time, and vulnerability of coastal areas make it difficult to effectively monitor and manage these important state and national resources using traditional data collection technologies such as discrete monitoring stations and field surveys. In general, these approaches provide only a sparse network of data over limited time and space scales and generally are expensive and labor-intensive. Products derived from spectral images obtained by remote sensing instruments provide a unique vantage point from which to examine the dynamic nature of coastal environments. A primary advantage of remote sensing is that the altitude of observation provides a large-scale synoptic view relative to traditional field measurements. Equally important, the use of remote sensing for a broad range of research and environmental applications is now common due to major advances in data availability, data transfer, and computer technologies. To facilitate the widespread use of remote sensing products in North Carolina, the UNC Coastal Studies Institute (UNC-CSI) is developing the capability to acquire, process, and analyze remotely sensed data from several remote sensing instruments. In particular, UNC-CSI is developing regional remote sensing algorithms to examine the mobilization, transport, transformation, and fate of materials between coupled terrestrial and coastal ocean systems. To illustrate this work, we present the basic principles of remote sensing of coastal waters in the context of deriving information that supports efficient and effective management of coastal resources. (PDF contains 4 pages)

A dynamic CGE modelling approach for analyzing trade-offs in climate change policy options: the case of Green Climate Fund

38 p.

Political Institutions, Technology and Growth: a dynamic panel approach

This paper investigates whether the effect of political institutions on sectoral economic performance is determined by the level of technological development of industries. Building on previous studies on the linkages among political institutions, technology and economic growth, we employ the dynamic panel Generalized Method of Moments (GMM) estimator for a sample of 4,134 country-industries from 61 industries and 89 countries over the 1990-2010 period. Our main findings suggest that changes of political institutions towards higher levels of democracy, political rights and civil liberties enhance economic growth in technologically developed industries. On the contrary, the same institutional changes might retard economic growth of those industries that are below a technological development threshold. Overall, these results give evidence of a technologically conditioned nature of political institutions to be growth-promoting.

Aquaculture technologies in Bangladesh: an assessment of technical and economic performance and producer behavior

This study evaluates the performance of a wide range of aquaculture systems in Bangladesh. It is by far the largest of its kind attempted to date. The purpose of this study was to identify and analyze the most important production systems, rather than to provide a nationally representative overview of the entire aquaculture sector of Bangladesh. As such, the study yields a huge amount of new information on production technologies that have never been thoroughly researched before. The study reveals an extremely diverse array of specialized, dynamic and rapidly evolving production technologies, adapted to a variety of market niches and local environmental conditions. This is a testament to the innovativeness of farmers and other value chain actors who have been the principal drivers of this development in Bangladesh. Data was collected from six geographical hubs. This survey was conducted from November 2011 to June 2012. Technological performance in terms of detailed input and output information, fish management practices, credit and marketing, and social and environmental issues were captured by the survey questionnaire, which had both open and closed format questions. The study generated insights that enable better understanding of aquaculture development in Bangladesh.

Oscillations in a decentralized economic network

The study of exchange markets dates back to LeonWalras's general equilibrium theory. Since then the economic market has been studied for its' equilibrium properties, fairness of allocations of private and public goods, and even the psychological incentives of participants. This paper studies the dynamics of an exchange economy built on a network of markets where consumers trade with suppliers to optimize utility. Viewing the market in as a decentralized network we study the system from the usual control theory point of view, evaluating the system's dynamic performance, stability and robustness. It is shown that certain consumer demand dynamics can lead to oscillations while others can converge to optimal allocations. © 2011 IFAC.

Analysis of spatio-temporal dynamic pattern and driving forces of urban land in China in 1990s using TM images and GIS

China has witnessed fast urban growth in the recent decade. This study analyzes spatio-temporal characteristics of urban expansion in China using satellite images and regionalization methods. Landsat TM images at three time periods, 1990/1991, 1995/1996, and 1999/2000, are interpreted to get 1:100000 vector land use datasets. The study calculates the urban land percentage and urban land expansion index of every 1 km(2) cell throughout China. The study divides China into 27 urban regions to conceive dynamic patterns of urban land changes. Urban development was achieving momentum in the western region, expanding more noticeably than in the previous five years, and seeing an increased growth percentage. Land use dynamic changes reflect the strong impacts of economic growth environments and macro-urban development policies. The paper helps to distinguish the influences of newly market-oriented forces from traditional administrative controls on China's urban expansion. (c) 2005 Elsevier Ltd. All rights reserved.

Managing dynamic competition

In many important high-technology markets, including software development, data processing, communications, aeronautics, and defense, suppliers learn through experience how to provide better service at lower cost. This paper examines how a buyer designs dynamic competition among rival suppliers to exploit learning economies while minimizing the costs of becoming locked in to one producer. Strategies for controlling dynamic competition include the handicapping of more efficient suppliers in procurement competitions, the protection and allocation of intellectual property, and the sharing of information among rival suppliers. (JEL C73, D44, L10).