This study identifies the factors influencing adoption of IPM practices and number of pesticide applications in vegetable farmers in Kenya. The sample size for this study includes 263 vegetable farmers. The survey was conducted in four counties of Kenya: Nyeri, Tharka Nithi, Nakuru and Bomet. The vegetables considered in this study are tomato, cabbage and French beans. Different econometric tools are used to analyze adoption of IPM practices and pesticide application for vegetables. It is found that experience in vegetable cultivation and number of livestock owned have a positive impact on the adoption of IPM practices. However, distance to the nearest town has a negative impact on adoption. Moreover, the number of times pesticides are applied to vegetables also declines as distance of the household from the nearest town increases. Farmers whose crops face less stress from insects and disease tend to apply pesticides fewer times as well. Results from this study indicate that being close to town is important for agricultural activities in general. Being farther away not only reduces the probability of IPM adoption but also reduces pesticide application. / Master of Science

<p>Betting under ordered forms has been around for a long time, but the recent increase in Internet betting and the large sums of money that are now involved makes it even more important for betting companies to have correct odds.</p><p> </p><p>The purpose of the essay is to calculate probabilities for outcomes of football games using a statistical model and to see if you can find better odds than a betting company.</p><p>The data contains the 380 games from the 2004/2005 season and the variables form, head-to-heads, league position, points, home/away, average attendance, promoted team, distance and final league position from previous season.</p><p> </p><p>After performing an ordered probit regression we only find the variable “form of the away team” to be significant at the 5 % level. We suspect the presence of multicollinearity and perform a VIF-test which confirms this. To fix this problem we perform a second ordered probit regression where a number of variables are combined to index variables. In the second regression we once again find only one significant variable. This time it is the variable “difference between home and away teams’ final league position”. A reason for the lack of significant variables could be the size of the data. A new model with five variables is examined and it results in four significant variables.</p><p> </p><p>The calculated odds pick the correct result in 200, 203 and 198 out of 380 games respectively, compared to 197 out of 380 for Unibet. Betting one krona on the lowest calculated odds from the second model will result in a positive yield for season 2004/2005 when using Unibet’s odds.</p> / <p>Vadslagning under ordnade former har funnits under en längre tid, men de senaste årens explosionsartade ökning av Internetspel och de stora summor som då omsätts har gjort det allt viktigare för spelbolagen att sätta korrekta odds.</p><p> </p><p>Syftet med uppsatsen är att med hjälp av en statistisk modell räkna ut sannolikheter för utfall i fotbollsmatcher och att undersöka om man kan hitta bättre odds än ett spelbolag.</p><p>Datamaterialet innefattar de 380 matcherna som spelades säsongen 2004/2005 samt de oberoende variablerna form, inbördes möten, tabellplacering, poängskörd, hemmaplan/bortaplan, publiksnitt, uppflyttat lag, avstånd och slutplacering.</p><p> </p><p>Efter utförd ordered probit regression erhåller vi endast en signifikant variabel vid en signifikansnivå på 5 %, nämligen ”bortalagets form”. Vi misstänker att det kan förekomma multikollinearitet och utför därför ett VIF-test som bekräftar detta. För att råda bot på detta problem genomför vi en andra ordered probit regression där flera variabler slås ihop till indexvariabler. I den andra regressionen får vi åter igen en enda signifikant variabel, men i detta fall är det variabeln ”differensen mellan hemma- och bortalagets slutplaceringar”. Ett skäl till att det inte blir fler signifikanta variabler misstänks vara storleken på datamaterialet. En ny modell med fem variabler undersöks och då blir fyra variabler signifikanta.</p><p> </p><p>De beräknade oddsen väljer rätt utfall i 200, 203 respektive 198 av 380 matcher för de tre modellerna mot Unibets 197 av 380 matcher. I modell 2 ger en spelad krona på utfallet med lägst beräknat odds positiv avkastning under säsongen vid spel hos Unibet.</p>

Betting under ordered forms has been around for a long time, but the recent increase in Internet betting and the large sums of money that are now involved makes it even more important for betting companies to have correct odds.   The purpose of the essay is to calculate probabilities for outcomes of football games using a statistical model and to see if you can find better odds than a betting company. The data contains the 380 games from the 2004/2005 season and the variables form, head-to-heads, league position, points, home/away, average attendance, promoted team, distance and final league position from previous season.   After performing an ordered probit regression we only find the variable “form of the away team” to be significant at the 5 % level. We suspect the presence of multicollinearity and perform a VIF-test which confirms this. To fix this problem we perform a second ordered probit regression where a number of variables are combined to index variables. In the second regression we once again find only one significant variable. This time it is the variable “difference between home and away teams’ final league position”. A reason for the lack of significant variables could be the size of the data. A new model with five variables is examined and it results in four significant variables.   The calculated odds pick the correct result in 200, 203 and 198 out of 380 games respectively, compared to 197 out of 380 for Unibet. Betting one krona on the lowest calculated odds from the second model will result in a positive yield for season 2004/2005 when using Unibet’s odds. / Vadslagning under ordnade former har funnits under en längre tid, men de senaste årens explosionsartade ökning av Internetspel och de stora summor som då omsätts har gjort det allt viktigare för spelbolagen att sätta korrekta odds.   Syftet med uppsatsen är att med hjälp av en statistisk modell räkna ut sannolikheter för utfall i fotbollsmatcher och att undersöka om man kan hitta bättre odds än ett spelbolag. Datamaterialet innefattar de 380 matcherna som spelades säsongen 2004/2005 samt de oberoende variablerna form, inbördes möten, tabellplacering, poängskörd, hemmaplan/bortaplan, publiksnitt, uppflyttat lag, avstånd och slutplacering.   Efter utförd ordered probit regression erhåller vi endast en signifikant variabel vid en signifikansnivå på 5 %, nämligen ”bortalagets form”. Vi misstänker att det kan förekomma multikollinearitet och utför därför ett VIF-test som bekräftar detta. För att råda bot på detta problem genomför vi en andra ordered probit regression där flera variabler slås ihop till indexvariabler. I den andra regressionen får vi åter igen en enda signifikant variabel, men i detta fall är det variabeln ”differensen mellan hemma- och bortalagets slutplaceringar”. Ett skäl till att det inte blir fler signifikanta variabler misstänks vara storleken på datamaterialet. En ny modell med fem variabler undersöks och då blir fyra variabler signifikanta.   De beräknade oddsen väljer rätt utfall i 200, 203 respektive 198 av 380 matcher för de tre modellerna mot Unibets 197 av 380 matcher. I modell 2 ger en spelad krona på utfallet med lägst beräknat odds positiv avkastning under säsongen vid spel hos Unibet.

Denna uppsats beräknar ett skuggpris för rädslan att gå ensam i mörkret i individens hemmakvarter samt undersöker skillnader mellan män och kvinnors skuggpriser för att vara mindre rädd. Tidigare studier som har använts sig av skuggpris för att beräkna rädsla har studerats och analyserats för att på bästa sätt kunna genomföra denna uppsats. Datamaterialet som använts i uppsatsen kommer från European Social Survey och består av 1791 observationer. Respondenterna fick i undersökningen svara på en skala mellan 1 till 4, där 1 var ’’mycket säker’’ och 4 var ’’mycket osäker’’ angående individens rädsla vid mörker. Skuggpriset motsvarar den summa av hushållets nettoinkomst som individen är villig att offra för att känna sig en enhet mindre rädd. Skuggpriset för att gå ensam i mörkret jämförs med män och kvinnors separata skuggpriser. Skuggpriset för att gå ensam i mörkret beräknades till 15 744 kronor. I uppsatsen skattades männens skuggpris till 12 881 kronor medan kvinnornas skuggpris blev 27 956 kronor. Därmed kan kvinnorna i Sverige tänka sig offra mer av sin månadsinkomst för att vara mindre rädd än männen i Sverige. Skillnaderna mellan män och kvinnors skuggpriser kan bero på att könen har separata psykologiska kostnader samt olika sociala roller i samhället. En kvinna tenderar att känna mer rädsla i vardagen än vad en man gör. Skillnaden mellan män och kvinnors skuggpriser skulle eventuellt kunna förklaras med att samhället kanske inte anser att en man ska känna rädsla och detta skulle kunna leda till att männen är villiga att betala mindre för att minska sin rädsla.

<p>Uppsatsen skapar en statistisk modell för beräkning av sannolikheter för utfall vid Allsvenska fotbollsmatcher. Modellens skattade sannolikheter för hemmavinst, oavgjort och bortavinst jämförs med utvalt spelbolag och visar på likvärdiga estimat. Utifrån de skattade sannolikheterna skapas odds som genererar lägre förluster än spelbolaget vid test utifrån ett spelbolags synvinkel. Sannolikheterna används även från en spelares perspektiv till att skapa ett spelsystem som genererar en positiv avkastning.</p>

Uppsatsen skapar en statistisk modell för beräkning av sannolikheter för utfall vid Allsvenska fotbollsmatcher. Modellens skattade sannolikheter för hemmavinst, oavgjort och bortavinst jämförs med utvalt spelbolag och visar på likvärdiga estimat. Utifrån de skattade sannolikheterna skapas odds som genererar lägre förluster än spelbolaget vid test utifrån ett spelbolags synvinkel. Sannolikheterna används även från en spelares perspektiv till att skapa ett spelsystem som genererar en positiv avkastning.

Potato farmers in Ecuador rely on chemical inputs to manage pests and optimize yields. IPM techniques are recommended to lower production costs, reduce exposure to pesticides, and improve the long-term sustainability of the agriculture system. We conducted a survey of 109 potato farmers in Carchi, Ecuador that included 30 Farmer Field School (FFS) participants, 28 farmers who had been exposed to FFS-participants, and 51 randomly selected farmers. Using an ordered probit model, the data were analyzed to identify determinants and constraints of adoption. Access to information through FFS was the main determinant of adoption of IPM, followed by field days, pamphlets, and exposure to FFS-participants. The study looked at the relative cost-effectiveness of information dissemination methods and found that field days and pamphlets have strong impacts on adoption considering their low cost of implementation. The only significant household variable was household size, where larger households adopted less IPM. Per capita land holdings were not significant in the model. There is evidence of farmer-to-farmer diffusion from FFS to non-FFS farmers. Further research is necessary to evaluate the nature and quality of information transfer between farmers. The study was limited by the small sample size and non-random selection of farmer respondents. / Master of Science

Many poor farmers, especially in Africa, have not adopted recent farming innovations to improve their yields. One theory is that poor farmers are risk averse and therefore do not invest in high risk high return innovations and that risk averse farmers will only adopt larger innovations if they experience success with small ones. Risk preferences were measured in two districts in Uganda (Tororo and Kapchorwa) where adoption of agricultural innovations has been slow, and where a program is underway to encourage use of conservation agriculture practices (CAPs) to reduce soil erosion and sequester carbon. An ordered lottery selection was used to measure risk preferences and an ordered probit model was estimated. Thirty five percent of a random sample of 200 farmers in Tororo (and fifty three percent of 200 farmers in Kapchorwa) made lottery choices that implied severe or extreme risk aversion. However there was no indication that risk preferences correlate with willingness to adopt new technologies (such as CAPs). Neither wealth nor previous success with technology adoption were found to correlate with farmers' risk preferences. / Master of Science / CCRA-6 (Economic and Impact Analysis)

[pt] A modelagem de dados que qualificam as transações de ativos financeiros, tais como, preço, spread de compra e venda, volume e duração, vem despertando o interesse de pesquisadores na área de finanças, levando a um aumento crescente do número de publicações referentes ao tema. As primeiras propostas se limitaram aos modelos de duração. Mais tarde, o impacto da duração sobre a volatilidade instantânea foi analisado. Recentemente, Manganelli (2002) incluiu dados referentes aos volumes transacionados dentro de um modelo vetorial. Neste estudo, nós estendemos o trabalho de Manganelli através da inclusão do spread de compra e venda num modelo vetorial autoregressivo, onde as médias condicionais do spread, volume, duração e volatilidade instantânea são descritas a partir de uma formulação exponencial chamada Exponential Multivariate Autoregressive Conditional Model (EMACM). Nesta nova proposta, não se fazem necessárias a adoção de quaisquer restrições nos parâmetros do modelo, o que facilita o procedimento de estimação por máxima verossimilhança e permite a utilização de testes de Razão de Verossimilhança na especificação da forma funcional do modelo (estrutura de interdependência). Em paralelo, a questão de antecipar movimentos nos preços de ativos financeiros é analisada mediante a utilização de um procedimento integrado, no qual, além da modelagem de dados financeiros de alta freqüência, faz-se uso de um modelo probit ordenado contemporâneo. O EMACM é empregado com o objetivo de capturar a dinâmica associada às variáveis e sua função de previsão é utilizada como proxy para a informação contemporânea necessária ao modelo de previsão de preços proposto. / [en] The availability of high frequency financial transaction data - price, spread, volume and duration -has contributed to the growing number of scientific articles on this topic. The first proposals were limited to pure duration models. Later, the impact of duration over instantaneous volatility was analyzed. More recently, Manganelli (2002) included volume into a vector model. In this document, we extended his work by including the bid-ask spread into the analysis through a vector autoregressive model. The conditional means of spread, volume and duration along with the volatility of returns evolve through transaction events based on an exponential formulation we called Exponential Multivariate Autoregressive Conditional Model (EMACM). In our proposal, there are no constraints on the parameters of the VAR model. This facilitates the maximum likelihood estimation of the model and allows the use of simple likelihood ratio hypothesis tests to specify the model and obtain some clues about the interdependency structure of the variables. In parallel, the problem of stock price forecasting is faced through an integrated approach in which, besides the modeling of high frequency financial data, a contemporary ordered probit model is used. Here, EMACM captures the dynamic that high frequency variables present, and its forecasting function is taken as a proxy to the contemporaneous information necessary to the pricing model.

In USA, despite recent efforts to improve work zone safety, the number of crashes and fatalities at work zones has increased continuously over several past years. For addressing the existing safety problems, a clear understanding of the characteristics of work zone crashes is necessary. This thesis summarized a research study focusing on work zone traffic crash analysis to investigate the characteristics of work zone crashes and to identify the factors contributing to injury severity at work zones. These factors included roadway design, environmental conditions, traffic conditions and vehicle/driver features. Especially, special population groups, which divided into older, middle Age, and young, were inspected. This study was based on history crash data from the Florida State, which were extracted from the Florida CAR (Crash Analysis Reporting) system. Descriptive statistics method was used to find the characteristics of crashes at work zones. After then, an injury severity predict model, using the ordered probit regression technology, was developed to investigate the impacts of various factors on different the injury severity at work zones. From the model, it can be concluded that some factors, including the road section with curve, alcohol/drugs involved, a high speed, angle crash and too young or old drivers are more likely to increase the probability of angle crashes. Based on the magnitudes of the variable coefficients, the factor of maximum posted speed have a great impact to injury severity, which shows restriction to driving speed is principle countermeasure for improving work zone safety.