881 resultados para Trade Price Index


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Chiefly tables.

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Description based on: Oct. 1979; title from caption.

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The purpose of this study is to develop econometric models to better understand the economic factors affecting inbound tourist flows from each of six origin countries that contribute to Hong Kong’s international tourism demand. To this end, we test alternative cointegration and error correction approaches to examine the economic determinants of tourist flows to Hong Kong, and to produce accurate econometric forecasts of inbound tourism demand. Our empirical findings show that permanent income is the most significant determinant of tourism demand in all models. The variables of own price, weighted substitute prices, trade volume, the share price index (as an indicator of changes in wealth in origin countries), and a dummy variable representing the Beijing incident (1989) are also found to be important determinants for some origin countries. The average long-run income and own price elasticity was measured at 2.66 and – 1.02, respectively. It was hypothesised that permanent income is a better explanatory variable of long-haul tourism demand than current income. A novel approach (grid search process) has been used to empirically derive the weights to be attached to the lagged income variable for estimating permanent income. The results indicate that permanent income, estimated with empirically determined relatively small weighting factors, was capable of producing better results than the current income variable in explaining long-haul tourism demand. This finding suggests that the use of current income in previous empirical tourism demand studies may have produced inaccurate results. The share price index, as a measure of wealth, was also found to be significant in two models. Studies of tourism demand rarely include wealth as an explanatory forecasting long-haul tourism demand. However, finding a satisfactory proxy for wealth common to different countries is problematic. This study indicates with the ECM (Error Correction Models) based on the Engle-Granger (1987) approach produce more accurate forecasts than ECM based on Pesaran and Shin (1998) and Johansen (1988, 1991, 1995) approaches for all of the long-haul markets and Japan. Overall, ECM produce better forecasts than the OLS, ARIMA and NAÏVE models, indicating the superiority of the application of a cointegration approach for tourism demand forecasting. The results show that permanent income is the most important explanatory variable for tourism demand from all countries but there are substantial variations between countries with the long-run elasticity ranging between 1.1 for the U.S. and 5.3 for U.K. Price is the next most important variable with the long-run elasticities ranging between -0.8 for Japan and -1.3 for Germany and short-run elasticities ranging between – 0.14 for Germany and -0.7 for Taiwan. The fastest growing market is Mainland China. The findings have implications for policies and strategies on investment, marketing promotion and pricing.

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This paper proposes arithmetic and geometric Paasche quality-adjusted price indexes that combine micro data from the base period with macro data on the averages of asset prices and characteristics at the index period.

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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.

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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 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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The study seeks to find out whether the real burden of the personal taxation has increased or decreased. In order to determine this, we investigate how the same real income has been taxed in different years. Whenever the taxes for the same real income for a given year are higher than for the base year, the real tax burden has increased. If they are lower, the real tax burden has decreased. The study thus seeks to estimate how changes in the tax regulations affect the real tax burden. It should be kept in mind that the progression in the central government income tax schedule ensures that a real change in income will bring about a change in the tax ration. In case of inflation when the tax schedules are kept nominally the same will also increase the real tax burden. In calculations of the study it is assumed that the real income remains constant, so that we can get an unbiased measure of the effects of governmental actions in real terms. The main factors influencing the amount of income taxes an individual must pay are as follows: - Gross income (income subject to central and local government taxes). - Deductions from gross income and taxes calculated according to tax schedules. - The central government income tax schedule (progressive income taxation). - The rates for the local taxes and for social security payments (proportional taxation). In the study we investigate how much a certain group of taxpayers would have paid in taxes according to the actual tax regulations prevailing indifferent years if the income were kept constant in real terms. Other factors affecting tax liability are kept strictly unchanged (as constants). The resulting taxes, expressed in fixed prices, are then compared to the taxes levied in the base year (hypothetical taxation). The question we are addressing is thus how much taxes a certain group of taxpayers with the same socioeconomic characteristics would have paid on the same real income according to the actual tax regulations prevailing in different years. This has been suggested as the main way to measure real changes in taxation, although there are several alternative measures with essentially the same aim. Next an aggregate indicator of changes in income tax rates is constructed. It is designed to show how much the taxation of income has increased or reduced from one year to next year on average. The main question remains: How aggregation over all income levels should be performed? In order to determine the average real changes in the tax scales the difference functions (difference between actual and hypothetical taxation functions) were aggregated using taxable income as weights. Besides the difference functions, the relative changes in real taxes can be used as indicators of change. In this case the ratio between the taxes computed according to the new and the old situation indicates whether the taxation has become heavier or easier. The relative changes in tax scales can be described in a way similar to that used in describing the cost of living, or by means of price indices. For example, we can use Laspeyres´ price index formula for computing the ratio between taxes determined by the new tax scales and the old tax scales. The formula answers the question: How much more or less will be paid in taxes according to the new tax scales than according to the old ones when the real income situation corresponds to the old situation. In real terms the central government tax burden experienced a steady decline from its high post-war level up until the mid-1950s. The real tax burden then drifted upwards until the mid-1970s. The real level of taxation in 1975 was twice that of 1961. In the 1980s there was a steady phase due to the inflation corrections of tax schedules. In 1989 the tax schedule fell drastically and from the mid-1990s tax schedules have decreased the real tax burden significantly. Local tax rates have risen continuously from 10 percent in 1948 to nearly 19 percent in 2008. Deductions have lowered the real tax burden especially in recent years. Aggregate figures indicate how the tax ratio for the same real income has changed over the years according to the prevailing tax regulations. We call the tax ratio calculated in this manner the real income tax ratio. A change in the real income tax ratio depicts an increase or decrease in the real tax burden. The real income tax ratio declined after the war for some years. In the beginning of the 1960s it nearly doubled to mid-1970. From mid-1990s the real income tax ratio has fallen about 35 %.

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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.