This thesis consists of three independent essays, unified by the common theme of the distributional impacts of government. The first paper estimates the price elasticity of demand for pharmaceuticals amongst high-income older people in Australia. It exploits a natural experiment by which some people gained entitlement to a price reduction through the Commonwealth Seniors Health Card (CSHC). The preferred model is a nonlinear Instrumental Variable (IV) difference-in-difference regression, estimated on repeated cross sectional survey data using the Generalised Method of Moments. No significant evidence is found for endogenous card take-up, and so cross-sectional estimates are also considered. Taking all of the results and possible sources of bias into account, the ??headline?? estimate is -0.1, implying that quantity demanded is not highly responsive to price. The elasticity estimate is a key input into the second paper which analyses the distributional impact of the CSHC. I consider the trade-off between moral hazard and risk pooling. There have been few previous attempts internationally to address this trade-off empirically for any health insurance scheme. The utility gain through risk-pooling is found to be negligible. However, the deadweight loss through moral hazard may be considerable. I also use an illustrative model to demonstrate the possible effects of the CSHC on inter-temporal savings behaviour. While the CSHC may induce some people to save, it may have the opposite effect on others. The net impact was not determined. The third paper estimates the Australian public sector wage premium. It includes a detailed critical review of the methods available to address this issue. The chosen approach is a quasi-differenced panel data model, estimated by nonlinear IV, which has many advantages over other methods and has not been used before for this topic. I find a positive average public sector wage premium for both sexes. The best estimates are 10.0% for men and 7.1% for women. The estimate for men is statistically significant (p < 0.04) and borders on significance for women (p < 0.07). No evidence is found to suggest that the public sector has an equalising effect on the wages of its workers.

Chapter 1 discusses the econometric pitfalls associated with the use of patent production functions to study the invention process. It then goes on to argue that a sound understanding of the invention process necessarily requires an understanding of the propensity to patent. The empirical analysis carried out in Chapter 1 seeks to explain the proportion of inventions patented – a potential metric for the propensity to patent – from an international sample of manufacturing firms. Chapter 2 proposes a methodology to filter out the noise induced by varying patent practices in the R&D-patent relationship. The methodology explicitly decomposes the patent-to-R&D ratio into its components of productivity and propensity. It is then applied to a novel data set of priority patent applications in four countries and six industries. Chapter 3 takes stock of the literature on the role of fees in patent systems while Chapter 4 presents estimates of the price elasticity of demand for patents at the trilateral offices (that is, in the U.S., Japan and Europe). The estimation of dynamic panel data models of patent applications suggests that the long-term price elasticity is about -0.30.

Denna uppsats behandlar de relativa prisökningar som skett för snusprodukter i Sverige och vill undersöka om dessa har lett till minskad efterfrågan som nationalekonomisk teori föreslår. Utifrån teori och tidigare forskning har en efterfrågemodell konstruerats för att möjliggöra en statistik undersökning. Variablerna som ingår i modellen är inhämtade från Statistiska centralbyråns prisenhet och Swedish Match AB och inkluderar prisuppgifter för varor, försäljningsstatistik och disponibel inkomst under tidsperioden 1999-2009. Resultaten från regressionsanalyser för tidsseriedata visar på att de ökade priserna har haft en negativ inverkan på efterfrågan på snus under den gällande tidsperioden, men att denna effekt varit förhållandevis liten.

This study analyzes consumers' behavioral responsiveness to changes in price and policy regarding residential electricity consumption, using a hybrid method of econometric analyses and energy market simulations with the National Energy Modeling System (NEMS). First, this study estimates price elasticities of residential electricity demand with the most recent Residential Energy Consumption Survey (RECS) data, collected in 2005, employing a conventional econometric model and a discrete/continuous choice model. Prior to the NEMS experiments with price shocks and consumers' behavioral features, this study uses NEMS to examine how energy policies would affect changes in retail electricity price in the future. When climate policies are implemented nationally, electricity prices are estimated to increase by 17% in 2030 with a carbon cap and trade initiatives and by 4% with Renewable Electricity Standards (RES). The short-run elasticity of demand estimated from the 2005 RECS is found to be in a range of -0.81 ~ -0.66, which is more elastic than the current NEMS assumption of -0.15. The 2005 RECS dataset details information about American households' energy consumption. This rich source of micro-level data complements the existing econometric analysis based on time series data. Electricity price (either census-division average price or household average price), annual income and number of rooms are found to be three major determinants of the level of electricity consumption. The difference in short-run price elasticity leads to a difference in social welfare estimates of energy policies and energy market forecasts. This study suggests that the estimate of social welfare loss caused by electricity price increase is overestimated if the elasticity is assumed to be smaller than the actual responsiveness. Supposing that 1) the short-run elasticity of -0.66 reflects the actual consumers' responsiveness to price changes in the present and future and 2) retail electricity prices permanently increase by 10%, the welfare loss caused by the price increases would be estimated 0.9 billion dollars less than the current estimates with the elasticity of -0.15. This result suggests that if people are assumed to be more elastic to price signals, the time it takes for a policy to accomplish its goal could be shorter. In addition to assessing potential savings expected from consumers' behavioral changes with the concept of price elasticity of demand in neoclassical economic theory, this study reviews economic and non-economic theories about behavioral features of energy consumers and discusses how existing information programs could be improved.

Based on a previous empirical study of the effect of a residential demand response program in Sala, Sweden, this project  investigated the economic consequences of consumer behaviour change after a demand-based time of use distribution tariff was employed. The economic consequences of consumers were proven to be disadvantageous in terms of unit electricity price. Consumers could achieve more electricity bill saving through stabilising their electricity consumption during peak hours, and this way bring least compromising of their comfort level. In order to estimate the price elasticity of the studies demand response program, a new method of estimation price elasticity was proposed. With this method, the intensity of demand response of the demand response program was estimated in terms of price elasticity. Regression analysis was also applied to find out the price incentives of consumer behaviour change. And the results indicated that the rise in electricity supply charge hardly contributes to load reduction, while the demand-based tariff constituted an advantageous solution on load demand management. However stronger demand response still requires better communication with customers and more incentives other than the rise in distribution tariff.

This study investigated the demand patterns of poor households during a period of rising prices. Focus was on three main constructs namely the poor, rising prices and the demand patterns. The study was on Bophelong, a township in South Africa. This study was conducted from an empirical, quantitative approach which was preceded by a literature review. The main objective of conducting the literature review was to provide a theoretical framework for questionnaire design and empirical work. Cross sectional data was collected at Bophelong households. On completion of the survey, the poor were selected from the non-poor by means of a poverty line. The poor were further divided into two categories, namely moderately poor and the very poor. Moderately poor households were categorised by an income ranging 50% to 99% inclusively of their household poverty line. The very poor households were categorised by an income in the range of 0 to 49% inclusively of their poverty line. Using the above division, the total poverty rate was 56% of the total sample, 26% being moderately poor and 30% very poor. The poverty gap ratio for all the poor in the sample was 0.48, meaning that on average, the poor needed 48% of their current income to reach their poverty line. This ratio was 0.29 for the moderately poor households and 0.69 for the very poor households. A logistic regression done on the determinants of poverty in Bophelong showed that household size, age of the household head, monthly household income and the employment status of the household head were significant in determining poverty. The monthly average household income in Bophelong was R2 910. For the moderately poor households it was R1 641 for the and R932 for the very poor households. Household size was 3.96 for the whole sample size, 2.97 for the non-poor households, 4.2 for the moderately poor households and 4.7 for the very poor households. The study revealed that demand patterns of the poor differ from those of the non-poor. In addition the moderately poor households‟ demand patterns differ from the very poor An analysis of the poor‟s demand patterns during rising prices: the case of Bophelong household. The greatest part of income of the poor is spent on basic food stuffs. The very poor spent more than half of their income (53%) on food. The study indicated that bread is a giffen good only to the very poor households where quantity demanded moves in the same direction with price. In the non-poor households, bread is regarded inferior. A commodity can be overly a necessity, but the degree of necessity differs with a households‟ economic status. In some cases, a commodity was a necessity in the very poor households but a luxury in the non-poor. The way households substitute one good for another depends on their income levels. In conclusion, the study recommends that for poverty alleviation policies to effectively target the very poor in reducing malnutrition and hunger, these very poor should be studied separetely from the poor households. This is because households of different poverty levels face different challenges. A more detailed and deeper study relating to the demand structure of the poor is recommended. There is also a need to explore the survival means of the poor as to direct policy actions aimed at alleviating poverty among the poor in general. / Thesis (PhD (Economics))--North-West University, Vaal Triangle Campus, 2013

The purpose of this research is to understand and explain the TFT LCD industry phenomenon of oversupply vs. shortage and its impacts on the prices and quantities of individual TFT LCD makers. Also, to look for any fixed effects (if any exist) due to specific company and due to specific time. We employ a fixed effect model to estimate impacts of individual traded quantity on price and impacts of individual price on traded quantity. Using the panel data covering 16 makers and 24 months, our results reveal that the TFT LCD panel is highly quantity inelastic of the traded price but greatly price elastic of the traded quantity. With regard to fixed effect, the empirical result reveals there were significant time effects of price for some periods of time while there were significant time effects of quantity for some sizes of panels. Supply and demand could be one of the factors determining the time effects. As to the company fixed effect, most of company fixed effects of quantity prices were found significant whereas company fixed effects of price were not. Market shares and country of origin can be significant factors determining the company fixed effect of quantity. Keywords: Panel Data, Fixed Effect Model, Quantity Elasticity, Price Elasticity, Company Fixed Effect, Time Fixed Effect, TFT LCD

This thesis consists of three independent essays, unified by the common theme of the distributional impacts of government. The first paper estimates the price elasticity of demand for pharmaceuticals amongst high-income older people in Australia. It exploits a natural experiment by which some people gained entitlement to a price reduction through the Commonwealth Seniors Health Card (CSHC). The preferred model is a nonlinear Instrumental Variable (IV) difference-in-difference regression, estimated on repeated cross sectional survey data using the Generalised Method of Moments. No significant evidence is found for endogenous card take-up, and so cross-sectional estimates are also considered. Taking all of the results and possible sources of bias into account, the ??headline?? estimate is -0.1, implying that quantity demanded is not highly responsive to price. The elasticity estimate is a key input into the second paper which analyses the distributional impact of the CSHC. I consider the trade-off between moral hazard and risk pooling. There have been few previous attempts internationally to address this trade-off empirically for any health insurance scheme. The utility gain through risk-pooling is found to be negligible. However, the deadweight loss through moral hazard may be considerable. I also use an illustrative model to demonstrate the possible effects of the CSHC on inter-temporal savings behaviour. While the CSHC may induce some people to save, it may have the opposite effect on others. The net impact was not determined. The third paper estimates the Australian public sector wage premium. It includes a detailed critical review of the methods available to address this issue. The chosen approach is a quasi-differenced panel data model, estimated by nonlinear IV, which has many advantages over other methods and has not been used before for this topic. I find a positive average public sector wage premium for both sexes. The best estimates are 10.0% for men and 7.1% for women. The estimate for men is statistically significant (p < 0.04) and borders on significance for women (p < 0.07). No evidence is found to suggest that the public sector has an equalising effect on the wages of its workers.

The objective of this study is to conduct a marketing mix modeling to measure the effectiveness of past marketing activities on the product sales using a time-varying effect model (TVEM) approach. The longitudinal intensive data for this study has come from a large ice cream manufacturer in USA. Traditionally, static regression models have been used to measure the effectiveness of marketing mix variables to predict sales. And, these models used to find the time independent effect of the covariate on the dependent variable. On the other hand, a dynamic model such as time-varying effect model takes time into consideration. Researchers can model the changes in the relationship between dependent and independent variables over time using time-varying effect model. This is the first study, where a time-varying effect model approach has been used to measure the effectiveness of marketing mix elements in the ice cream industry. In addition, we have compared the predictive validity of both static and dynamic models using this data set.

O planejamento de produção é um elemento essencial para as empresas, pois permite definir os volumes a serem produzidos, conforme a estimativa de demanda e a capacidade produtiva disponível. Este trabalho contribui para o planejamento da produção, integrando variáveis e parâmetros que podem ajudar na maximização do resultado econômico das organizações. Esta dissertação apresenta três objetivos principais relacionados a esse tema: (i) identificar os problemas e as variáveis que precisam ser analisadas no desenvolvimento de métodos que se adéquam às necessidades das áreas envolvidas; (ii) desenvolver algoritmo para integrar as variáveis identificadas e os dados empresariais, de forma a viabilizar a aplicação do modelo, baseado em programação matemática e distribuições de probabilidade; (iii) aplicar os modelos propostos, a fim de avaliar sua utilidade e discutir os resultados obtidos. O estudo realizado revela a importância do uso de métodos formais de planejamento da produção integrados à definição do preço do produto. A definição de preços ou volumes de produção diferente dos valores ótimos pode afetar substancialmente o lucro global do sistema produtivo. / Production planning is an essential tool for companies, since it establishes the volumes to be produced, according to estimated demand and available production capacity. This work contributes with production planning field by integrating variables and parameters that impact the economic results of the organizations. This study presents three main objectives: (i) identification of issues and variables that need to be analyzed to develop methods suited to the needs of the areas involved, (ii) development of algorithms to integrate the identified variables and business data, in order to enable the application of the model, based on mathematical programming and probability distributions, (iii) application of the proposed models to evaluate their usefulness and discuss results. The study reveals the importance of using production planning formal methods that integrate products’ prices. The establishment of prices or production volumes different from optimum values may substantially affect production system global profit.