James Vercammen

Climate change is a long-term shift in the average weather conditions that threatens settlements, societies, and industries. Agriculture is one of the most climate-sensitive industries since the production in this sector is highly dependent on various weather factors. The main objective of this study is to evaluate the economic impact of climate change on Canadian Prairie agriculture using the well-known Ricardian model. The Ricardian model is best described as a hedonic regression of farmland value on an assortment of climatic and non-climatic variables. This model is widely used in economic analysis because it captures farmers’ adaptation strategies to climate change. To estimate the parameters of the Ricardian model, three methods are utilized: pooled weighted least squared (WLS), random effects, and spatial random effects. The estimated coefficients are used to predict the impact of three potential climate and price change scenarios on farmland value in the Canadian Prairies. The main contributions of this study relative to existing studies are: the use of updated data, the inclusion of expected prices rather than actual prices in the model, and the utilization of spatial econometrics methods to estimate the model.The estimated marginal impacts of climate demonstrate that an increase in rainfall and winter, spring, and fall temperatures will increase farmland value; the effect is opposite for July temperature. The signs of the marginal impacts of rainfall and July temperature reveal that water availability plays a very important role in crop production on the Canadian Prairies.Overall, climate change is predicted to increase the value of farm land on the Canadian Prairies by an average of 0.9% to 3.87% annually. However, the northern part of Saskatchewan and the north-eastern part of Alberta are forecasted to experience a decrease in farmland value under a medium climate change scenario. The current analysis predicts that farm welfare in the Prairies will increase by about $1.14 - $4.1 billion annually as a result of climate change. This suggests that with proper adaptations, climate change can be beneficial for Prairie agriculture.

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The integration of spatially separated markets was accelerated by intense trade in the last few decades. China started to open its markets since 1978 and now it plays an important role in world trade. However, China’s impact is less pronounced on agricultural commodity markets, and its impact varies across different commodities. This study discusses the prices performance of corn, soybean, and wheat in China and the U.S. We examine the integration process of Chinese agricultural commodity markets after China’s entry to WTO (i.e. 2004-2012). This study applies the cointegration test with and without a structural change. We detect the cointegration relationship between soybean prices in China and the U.S., but we observe such relationship does not exist in corn and wheat markets within China and the U.S.

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Business innovation is a powerful source of productivity increase and economic growth. Lack of financing at commercialization stages of innovation development often dooms socially valuable innovations to failure. To address pre-commercialization market failure, public agencies assist entrepreneurs with financial resources through commercialization competition mechanisms. Public agencies administering commercialization competitions may have dual objectives. Ex ante, they aim to induce entrepreneurs to invest an efficient amount of resources, accounting for resource costs and the associated expected social benefits. Ex post, commercialization awards should be allocated so that the expected social welfare aggregated across all projects is maximized. This would likely entail maximizing the number of socially valuable projects which are successfully commercialized. The objective of this thesis is to demonstrate that the ex ante and ex post objectives of a public agency may be in conflict. The ex ante award allocation criteria announced when the competition is launched may differ from the ex post award criteria retained by the agency as private information. Thus, agency decision-making may be time inconsistent. To achieve this objective, first, a theoretical model of commercialization competition was developed based on a real-world prototype, New Ventures Competition, administered by the British Columbia Innovation Council. It demonstrates that the competition causes underinvestment on the entrepreneurs’ side and allows the agency to deviate from ex ante announced award allocation criteria. Second, since time inconsistency is related to competition fairness, an experiment was conducted to determine whether respondents trade the competition fairness for “greater social good”. It was established that when respondents are aware of both entrepreneurs’ financial contributions to projects and their financial need, and when they are put into situation where maximization of social welfare is in conflict with maintaining ethical values, respondents tend to deviate from an allocation decision based on ex ante announced criteria. Third, it was established that when respondents face a particularly strong ethical trade-off, the higher the grades they received on average in their last year at school, the less they tend to change their original rankings to assist in the commercialization of comparatively lower quality projects at the expense of competition fairness.

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In response to the rampant and high volatility in rice prices relative to other grains over the past few decades and calls by governments for tighter control and regulation on futures trading to limit speculation and curtail volatility, this work evaluates the performance of the rice futures market in United State in terms of its impact on the nation’s rice cash price volatility. This study presents a refined form of Milton Friedman’s original theory (1953) that speculation leads to less volatility unless it is carried out by irrational speculators. It will test this theory empirically using time series econometrics. Generalized autoregressive conditional heteroskedasticity (GARCH) is used to measure volatility of the price of rice. Vector autoregressive (VAR) models are deployed to measure the impact of trading activity on cash price volatility through Granger Causality test, forecast error variance decomposition (FEVD), and impulse response (IR) methods. Results show that rice cash price volatility after the introduction of the rice futures market on the Chicago Board of Trade is lowered by 51%. The Granger Causality test also indicates that sudden changes in the futures market trading activity (proxy for the presence of irrational speculators) cause higher volatility in the cash market. The FEVD, and IR methods indicate that a sudden rise in non-commercial open interest has a larger impact on cash price volatility than changes in trading volume.

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The objective of this thesis is to examine reasons for boom-and-bust cycles of blueberries in British Columbia as a case study by performing financial analysis, estimating a price elasticity of blueberry supply, and simulating changes in the price and acreage of blueberries. In order to achieve the above stated objectives, three models will be constructed. First, a business planning spreadsheet model is constructed in order to analyze the profitability of blueberry investment in British Columbia. The model studies the profitability of blueberry production with high prices during the boom period and low prices during the bust period. The results demonstrate that farmers make fairly good returns on investment during times of high prices in the blueberry boom, while the returns in the bust period can barely cover their production costs.Second, the dynamic supply response model of Nerlove (1958) is adopted in order to estimate a reduced form supply function for blueberry producers in British Columbia. The results show that blueberry farmers had an inelastic response to price changes in the short run and a highly elastic response to price changes in the long run. These findings help to explain why the acreage of blueberries has rapidly expanded over the past decade. Third, on the basis of the estimated price elasticities of blueberry supply, the cobweb model is used in order to simulate boom-and-bust cycles in the price and acreage of blueberries. The simulation adopts the convergent type of cobweb because the demand elasticity of blueberries is expected to be elastic. The result of simulations indicates that the more elastic the demand curve is, the quicker the price and acreage of blueberries converge to a steady state.

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