880 resultados para Consumer price index
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In this thesis, we evaluate consumer purchase behaviour from the perspective of heuristic decision making. Heuristic decision processes are quick and easy mental shortcuts, adopted by individuals to reduce the amount of time spent in decision making. In particular, we examine those heuristics which are caused by framing – prospect theory and mental accounting, and examine these within price related decision scenarios. The impact of price framing on consumer behaviour has been studied under the broad umbrella of reference price, which suggests that decision makers use reference points as standards of comparison when making a purchase decision. We investigate four reference points - a retailer's past prices, a competitor's current prices, a competitor's past prices, and consumers' expectation of immediate future price changes, to further our understanding of the impact of price framing on mental accounting, and in turn, contribute to the growing body of reference price literature in Marketing research. We carry out experiments in which levels of price frame and monetary outcomes are manipulated in repeated measures analysis of variance (ANOVA). Our results show that where these reference points are clearly specified in decision problems, price framing significantly affects consumers' perceptions of monetary gains derived through discounts, and leads to reversals in consumer preferences. We also found that monetary losses were not sensitive to price frame manipulations.
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Principal Topic: Entrepreneurship is key to employment, innovation and growth (Acs & Mueller, 2008), and as such, has been the subject of tremendous research in both the economic and management literatures since Solow (1957), Schumpeter (1934, 1943), and Penrose (1959). The presence of entrepreneurs in the economy is a key factor in the success or failure of countries to grow (Audretsch and Thurik, 2001; Dejardin, 2001). Further studies focus on the conditions of existence of entrepreneurship, influential factors invoked are historical, cultural, social, institutional, or purely economic (North, 1997; Thurik 1996 & 1999). Of particular interest, beyond the reasons behind the existence of entrepreneurship, are entrepreneurial survival and good ''performance'' factors. Using cross-country firm data analysis, La Porta & Schleifer (2008) confirm that informal micro-businesses provide on average half of all economic activity in developing countries. They find that these are utterly unproductive compared to formal firms, and conclude that the informal sector serves as a social security net ''keep[ing] millions of people alive, but disappearing over time'' (abstract). Robison (1986), Hill (1996, 1997) posit that the Indonesian government under Suharto always pointed to the lack of indigenous entrepreneurship , thereby motivating the nationalisation of all industries. Furthermore, the same literature also points to the fact that small businesses were mostly left out of development programmes because they were supposed less productive and having less productivity potential than larger ones. Vial (2008) challenges this view and shows that small firms represent about 70% of firms, 12% of total output, but contribute to 25% of total factor productivity growth on average over the period 1975-94 in the industrial sector (Table 10, p.316). ---------- Methodology/Key Propositions: A review of the empirical literature points at several under-researched questions. Firstly, we assess whether there is, evidence of small family-business entrepreneurship in Indonesia. Secondly, we examine and present the characteristics of these enterprises, along with the size of the sector, and its dynamics. Thirdly, we study whether these enterprises underperform compared to the larger scale industrial sector, as it is suggested in the literature. We reconsider performance measurements for micro-family owned businesses. We suggest that, beside productivity measures, performance could be appraised by both the survival probability of the firm, and by the amount of household assets formation. We compare micro-family-owned and larger industrial firms' survival probabilities after the 1997 crisis, their capital productivity, then compare household assets of families involved in business with those who do not. Finally, we examine human and social capital as moderators of enterprises' performance. In particular, we assess whether a higher level of education and community participation have an effect on the likelihood of running a family business, and whether it has an impact on households' assets level. We use the IFLS database compiled and published by RAND Corporation. The data is a rich community, households, and individuals panel dataset in four waves: 1993, 1997, 2000, 2007. We now focus on the waves 1997 and 2000 in order to investigate entrepreneurship behaviours in turbulent times, i.e. the 1997 Asian crisis. We use aggregate individual data, and focus on households data in order to study micro-family-owned businesses. IFLS data covers roughly 7,600 households in 1997 and over 10,000 households in 2000, with about 95% of 1997 households re-interviewed in 2000. Households were interviewed in 13 of the 27 provinces as defined before 2001. Those 13 provinces were targeted because accounting for 83% of the population. A full description of the data is provided in Frankenberg and Thomas (2000), and Strauss et alii (2004). We deflate all monetary values in Rupiah with the World Development Indicators Consumer Price Index base 100 in 2000. ---------- Results and Implications: We find that in Indonesia, entrepreneurship is widespread and two thirds of households hold one or several family businesses. In rural areas, in 2000, 75% of households run one or several businesses. The proportion of households holding both a farm and a non farm business is higher in rural areas, underlining the reliance of rural households on self-employment, especially after the crisis. Those businesses come in various sizes from very small to larger ones. The median business production value represents less than the annual national minimum wage. Figures show that at least 75% of farm businesses produce less than the annual minimum wage, with non farm businesses being more numerous to produce the minimum wage. However, this is only one part of the story, as production is not the only ''output'' or effect of the business. We show that the survival rate of those businesses ranks between 70 and 82% after the 1997 crisis, which contrasts with the 67% survival rate for the formal industrial sector (Ter Wengel & Rodriguez, 2006). Micro Family Owned Businesses might be relatively small in terms of production, they also provide stability in times of crisis. For those businesses that provide business assets figures, we show that capital productivity is fairly high, with rates that are ten times higher for non farm businesses. Results show that households running a business have larger family assets, and households are better off in urban areas. We run a panel logit model in order to test the effect of human and social capital on the existence of businesses among households. We find that non farm businesses are more likely to appear in households with higher human and social capital situated in urban areas. Farm businesses are more likely to appear in lower human capital and rural contexts, while still being supported by community participation. The estimation of our panel data model confirm that households are more likely to have higher family assets if situated in urban area, the higher the education level, the larger the assets, and running a business increase the likelihood of having larger assets. This is especially true for non farm businesses that have a clearly larger and more significant effect on assets than farm businesses. Finally, social capital in the form of community participation also has a positive effect on assets. Those results confirm the existence of a strong entrepreneurship culture among Indonesian households. Investigating survival rates also shows that those businesses are quite stable, even in the face of a violent crisis such as the 1997 one, and as a result, can provide a safety net. Finally, considering household assets - the returns of business to the household, rather than profit or productivity - the returns of business to itself, shows that households running a business are better off. While we demonstrate that uman and social capital are key to business existence, survival and performance, those results open avenues for further research regarding the factors that could hamper growth of those businesses in terms of output and employment.
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OBJECTIVE: To assess changes in the cost and availability of a standard basket of healthy food items (the Healthy Food Access Basket [HFAB]) in Queensland. METHODS: Analysis of five cross-sectional surveys (1998, 2000, 2001, 2004 and 2006) describes changes over time. Eighty-nine stores in five remoteness categories were surveyed during May 2006. For the first time a sampling framework based on randomisation of towns throughout the state was applied and the survey was conducted by Queensland Treasury. RESULTS: Compared with the costs in major cities, in 2006 the mean cost of the HFAB was $107.81 (24.2%) higher in very remote stores in Queensland, but $145.57 (32.6%) higher in stores more than 2,000 kilometres from Brisbane. Over six years the cost of the HFAB has increased by around 50% ($148.87) across Queensland and, where data was available, by more than the cost of less healthy alternatives. The Consumer Price Index for food in Brisbane increased by 32.5% over the same period. CONCLUSIONS AND IMPLICATIONS: Australians, no matter where they live, need access to affordable, healthy food. Issues of food security in the face of rising food costs are of concern particularly in the current global economic downturn. There is an urgent need to nationally monitor, but also sustainably address the factors affecting the price of healthy foods, particularly for vulnerable groups who suffer a disproportionate burden of poor health.
Resumo:
Objective: To assess changes in the cost and availability of a standard basket of healthy food items (the Healthy Food Access Basket [HFAB]) in Queensland over time. Design and participants: A series of four cross-sectional surveys (in 1998, 2000, 2001 and 2004) describing the cost and availability of foods in the HFAB over time. In the latest survey, 97 Queensland food stores across the five Australian Bureau of Statistics remoteness categories were compared. Main outcome measures: Cost comparisons for HFAB items by remoteness category for the 97 stores surveyed in 2004; changes in cost and availability of foods in the 81 stores surveyed since 2000; comparisons of food prices in the 56 stores surveyed in 1998, 2000, 2001 and 2004. Results: In 2004, the Queensland mean cost of the HFAB was $395.28 a fortnight. The cost of the HFAB was 29.6%($113.89) higher in “very remote” areas than in “major cities” (P<0.001). Between 2001 and 2004, the Queensland mean cost of the HFAB increased by 14.0% ($48.45), while in very remote areas the cost increased by 18.0% ($76.93) (P<0.001). Since 2000, the annualised per cent increase in cost of the HFAB has been higher than the increase in Consumer Price Index for food in Brisbane. The cost of healthy foods has risen more than the cost of some less nutritious foods, so that the latter are now relatively more affordable. Conclusions: Consumers, particularly those in very remote locations, need to pay substantially more for basic healthy foods than they did a few years ago. Higher prices are likely to be a barrier to good health among people of low socioeconomic status and other vulnerable groups. Interventions to make basic healthy food affordable and accessible to all would help reduce the high burden of chronic disease.
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This study is the first to describe disparity and change in the food supply between metropolitan, rural and remote stores by Accessibility/Remoteness Index of Australia (ARIA)1 category. A total of 92 stores (97% response rate) within five aggregate ARIA categories participated throughout Queensland in 2000. There was a strong association between ARIA category and the cost of the basket of basic foods, with prices being significantly higher (20% and 31% respectively) in the ‘remote’ and ‘very remote’ categories than in the ‘highly accessible’ category. The association with ARIA was less marked for fruit and vegetables than for other food groups, but not for tobacco and take-away food items. Basic food items were less available in the more remote stores. Over the past two years, relative improvements in food prices have been seen in stores in the ‘very remote’ category, with observed increases less than the consumer price index (CPI) for food. Some factors which may have contributed to this improvement are discussed.
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This study uses information based on published ATO material and represents the extent of tax-deductible donations made and claimed by Australian individual taxpayers (i.e. not including corporate entities or trusts) to DGRs, at Item D9 Gifts or Donations, in their income tax returns for the 2011-12 income year. The total amount claimed as tax-deductible donations in 2011-12 was $2.24 billion (compared to $2.21 billion in 2010-11), representing 6.85% of all personal taxpayer deductions. Since 1978-79, the actual total tax-deductible donations claimed by Australian individual taxpayers has outpaced inflation-adjusted total tax-deductible donations, measured against the Consumer Price Index. The average tax-deductible donation claimed in 2011-12 increased to $494.25, but the absolute number and percentage of taxpayers claiming donations dropped (to 4.54 million or 35.62%). Analysis is given of individual taxpayers' donation claiming by Gender, State of Residence, Postcode, Income Band, Industry of employment, and Occupation.
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In the thesis we consider inference for cointegration in vector autoregressive (VAR) models. The thesis consists of an introduction and four papers. The first paper proposes a new test for cointegration in VAR models that is directly based on the eigenvalues of the least squares (LS) estimate of the autoregressive matrix. In the second paper we compare a small sample correction for the likelihood ratio (LR) test of cointegrating rank and the bootstrap. The simulation experiments show that the bootstrap works very well in practice and dominates the correction factor. The tests are applied to international stock prices data, and the .nite sample performance of the tests are investigated by simulating the data. The third paper studies the demand for money in Sweden 1970—2000 using the I(2) model. In the fourth paper we re-examine the evidence of cointegration between international stock prices. The paper shows that some of the previous empirical results can be explained by the small-sample bias and size distortion of Johansen’s LR tests for cointegration. In all papers we work with two data sets. The first data set is a Swedish money demand data set with observations on the money stock, the consumer price index, gross domestic product (GDP), the short-term interest rate and the long-term interest rate. The data are quarterly and the sample period is 1970(1)—2000(1). The second data set consists of month-end stock market index observations for Finland, France, Germany, Sweden, the United Kingdom and the United States from 1980(1) to 1997(2). Both data sets are typical of the sample sizes encountered in economic data, and the applications illustrate the usefulness of the models and tests discussed in the thesis.
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This study is divided into two parts: a methodological part and a part which focuses on the saving of households. In the 1950 s both the concepts as well as the household surveys themselves went through a rapid change. The development of national accounts was motivated by the Keynesian theory and the 1940 s and 1950 s were an important time for the development of the national accounts. Before this, saving was understood as cash money or money deposited in bank accounts but the changes in this era led to the establishment of the modern saving concept. Separate from the development of national accounts, household surveys were established. Household surveys have been conducted in Finland from the beginning of the 20th century. At that time surveys were conducted in order to observe the working class living standard and as a result, these were based on the tradition of welfare studies. Also a motivation for undertaking the studies was to estimate weights for the consumer price index. A final reason underpinning the government s interest in observing this data regarded whether there were any reasons for the working class to become radicalised and therefore adopt revolutionary ideas. As the need for the economic analysis increased and the data requirements underlying the political decision making process also expanded, the two traditions and thus, the two data sources started to integrate. In the 1950s the household surveys were compiled distinctly from the national accounts and they were virtually unaffected by economic theory. The 1966 survey was the first study that was clearly motivated by national accounts and saving analysis. This study also covered the whole population rather than it being limited to just part of it. It is essential to note that the integration of these two traditions is still continuing. This recently took a big step forward as the Stiglitz, Sen and Fitoussi Committee Report was introduced and thus, the criticism of the current measure of welfare was taken seriously. The Stiglitz report emphasises that the focus in the measurement of welfare should be on the households and the macro as well as micro perspective should be included in the analysis. In this study the national accounts are applied to the household survey data from the years 1950-51, 1955-56 and 1959-60. The first two studies cover the working population of towns and market towns and the last survey covers the population of rural areas. The analysis is performed at three levels: macro economic level, meso level, i.e. at the level of different types of households, and micro level, i.e. at the level of individual households. As a result it analyses how the different households saved and consumed and how that changed during the 1950 s.
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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).
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A presente dissertação discute o repasse cambial para o IPCA na economia brasileira durante o período compreendido entre janeiro de 1999 e dezembro de 2007. A ampla maioria dos trabalhos que versam sobre este tema aborda a redução do repasse após a adoção do regime de metas de inflação e/ou tem como único foco o impacto das desvalorizações cambiais no aumento dos índices de preços. Este trabalho, por outro lado, aborda de maneira explícita o papel da valorização do Real sobre a variação do IPCA no período recente, configurando o que denominamos de repasse cambial reverso. Para tanto, estimamos o repasse cambial por meio de um modelo de vetores auto-regressivos tanto para o referido período (1999-2007), quanto para outros dois recortes temporais: entre janeiro de 1999 e junho 2003 (amostra 1), período no qual se verifica uma tendência de desvalorização cambial e aumento de preços; e de julho de 2003 a dezembro de 2007 (amostra 2), período caracterizado pelo processo inverso, de valorização da taxa de câmbio e de cumprimento das metas de inflação na maioria dos anos. Os principais resultados foram: (i) no longo prazo os coeficientes de repasse cambial para o IPCA para as duas amostras foram superiores àqueles verificados para o período completo; e (ii) o repasse estimado para a amostra 2 foi bem elevado, ainda que inferior àquele obtido para a amostra 1. Estes resultados reforçam o argumento de que a taxa de câmbio desempenhou um papel proeminente no controle da inflação no período 2003-2007.
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A number of studies have found an asymmetric response of consumer price index inflation to the output gap in the US in simple Phillips curve models. We consider whether there are similar asymmetries in mark-up pricing models, that is, whether the mark-up over producers' costs also depends upon the sign of the (adjusted) output gap. The robustness of our findings to the price series is assessed, and also whether price-output responses in the UK are asymmetric.
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The gradual changes in the world development have brought energy issues back into high profile. An ongoing challenge for countries around the world is to balance the development gains against its effects on the environment. The energy management is the key factor of any sustainable development program. All the aspects of development in agriculture, power generation, social welfare and industry in Iran are crucially related to the energy and its revenue. Forecasting end-use natural gas consumption is an important Factor for efficient system operation and a basis for planning decisions. In this thesis, particle swarm optimization (PSO) used to forecast long run natural gas consumption in Iran. Gas consumption data in Iran for the previous 34 years is used to predict the consumption for the coming years. Four linear and nonlinear models proposed and six factors such as Gross Domestic Product (GDP), Population, National Income (NI), Temperature, Consumer Price Index (CPI) and yearly Natural Gas (NG) demand investigated.
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Desde a implantação do sistema de metas de inflação em julho de 1999, o Banco Central (BC) tem utilizado para monitorar a política monetária um número crescente de indicadores, dentre os quais, incluem-se as medidas de núcleo de inflação. O objetivo é obter uma informação mais precisa sobre o curso da inflação no país e, consequentemente, sobre o futuro da política monetária. Além do Banco Central, muitas instituições financeiras utilizam medidas de núcleo para orientar suas estimativas em relação ao comportamento da inflação no país. Deste modo, esta dissertação faz uma avaliação dos núcleos de inflação utilizando os principais testes estatísticos e econométricos sugeridos pela literatura econômica e propõe ainda novos indicadores para o Brasil.
Resumo:
Este trabalho compara modelos de séries temporais para a projeção de curto prazo da inflação brasileira, medida pelo Índice de Preços ao Consumidor Amplo (IPCA). Foram considerados modelos SARIMA de Box e Jenkins e modelos estruturais em espaço de estados, estimados pelo filtro de Kalman. Para a estimação dos modelos, foi utilizada a série do IPCA na base mensal, de março de 2003 a março de 2012. Os modelos SARIMA foram estimados no EVIEWS e os modelos estruturais no STAMP. Para a validação dos modelos para fora da amostra, foram consideradas as previsões 1 passo à frente para o período de abril de 2012 a março de 2013, tomando como base os principais critérios de avaliação de capacidade preditiva propostos na literatura. A conclusão do trabalho é que, embora o modelo estrutural permita, decompor a série em componentes com interpretação direta e estudá-las separadamente, além de incorporar variáveis explicativas de forma simples, o desempenho do modelo SARIMA para prever a inflação brasileira foi superior, no período e horizonte considerados. Outro importante aspecto positivo é que a implementação de um modelo SARIMA é imediata, e previsões a partir dele são obtidas de forma simples e direta.
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Outliers são observações que parecem ser inconsistentes com as demais. Também chamadas de valores atípicos, extremos ou aberrantes, estas inconsistências podem ser causadas por mudanças de política ou crises econômicas, ondas inesperadas de frio ou calor, erros de medida ou digitação, entre outras. Outliers não são necessariamente valores incorretos, mas, quando provenientes de erros de medida ou digitação, podem distorcer os resultados de uma análise e levar o pesquisador à conclusões equivocadas. O objetivo deste trabalho é estudar e comparar diferentes métodos para detecção de anormalidades em séries de preços do Índice de Preços ao Consumidor (IPC), calculado pelo Instituto Brasileiro de Economia (IBRE) da Fundação Getulio Vargas (FGV). O IPC mede a variação dos preços de um conjunto fixo de bens e serviços componentes de despesas habituais das famílias com nível de renda situado entre 1 e 33 salários mínimos mensais e é usado principalmente como um índice de referência para avaliação do poder de compra do consumidor. Além do método utilizado atualmente no IBRE pelos analistas de preços, os métodos considerados neste estudo são: variações do Método do IBRE, Método do Boxplot, Método do Boxplot SIQR, Método do Boxplot Ajustado, Método de Cercas Resistentes, Método do Quartil, do Quartil Modificado, Método do Desvio Mediano Absoluto e Algoritmo de Tukey. Tais métodos foram aplicados em dados pertencentes aos municípios Rio de Janeiro e São Paulo. Para que se possa analisar o desempenho de cada método, é necessário conhecer os verdadeiros valores extremos antecipadamente. Portanto, neste trabalho, tal análise foi feita assumindo que os preços descartados ou alterados pelos analistas no processo de crítica são os verdadeiros outliers. O Método do IBRE é bastante correlacionado com os preços alterados ou descartados pelos analistas. Sendo assim, a suposição de que os preços alterados ou descartados pelos analistas são os verdadeiros valores extremos pode influenciar os resultados, fazendo com que o mesmo seja favorecido em comparação com os demais métodos. No entanto, desta forma, é possível computar duas medidas através das quais os métodos são avaliados. A primeira é a porcentagem de acerto do método, que informa a proporção de verdadeiros outliers detectados. A segunda é o número de falsos positivos produzidos pelo método, que informa quantos valores precisaram ser sinalizados para um verdadeiro outlier ser detectado. Quanto maior for a proporção de acerto gerada pelo método e menor for a quantidade de falsos positivos produzidos pelo mesmo, melhor é o desempenho do método. Sendo assim, foi possível construir um ranking referente ao desempenho dos métodos, identificando o melhor dentre os analisados. Para o município do Rio de Janeiro, algumas das variações do Método do IBRE apresentaram desempenhos iguais ou superiores ao do método original. Já para o município de São Paulo, o Método do IBRE apresentou o melhor desempenho. Em trabalhos futuros, espera-se testar os métodos em dados obtidos por simulação ou que constituam bases largamente utilizadas na literatura, de forma que a suposição de que os preços descartados ou alterados pelos analistas no processo de crítica são os verdadeiros outliers não interfira nos resultados.