An analysis of consumer panel data

In terms of collecting comprehensive panel expenditure data, there are trade-offs to be made in terms of the demands imposed on respondents and the level of detail and spending coverage collected. Existing comprehensive spending data tends to be cross-sectional whilst panel studies include only limited expenditure questions that record spending only as broad aggregates. More recently, economists have begun to use spending information collected by market research companies that records very detailed spending down to the barcode level from a panel of households, usually recorded by in-home barcode scanners, which may provide considerable advantages over existing data more commonly used in social sciences. However, there has not been a comprehensive assessment of the strengths and weaknesses of this kind of data collection method and the potential implications of survey mode on the recorded data. This paper seeks to address this, by an in-depth examination of scanner data from one company, Taylor Nelson Sofres (TNS), on grocery purchases over a five-year period. We assess how far the ongoing demands of participation inherent in this kind of survey lead to 'fatigue' in respondents' recording of their spending and compare the demographic representativeness of the data to the well-established Expenditure and Food Survey (EFS), constructing weights for the TNS that account for observed demographic differences. We also look at demographic transitions, comparing the panel aspect of the TNS to the British Household Panel Study (BHPS). We examine in detail the expenditure data in the TNS and EFS surveys and discuss the implications of this method of data collection for survey attrition. Broadly, we suggest that problems of fatigue and attrition may not be so severe as may be expected, though there are some differences in expenditure levels (and to some extent patterns of spending) that cannot be attributed to demographic or time differences in the two surveys alone and may be suggestive of survey mode effects. Demographic transitions appear to occur less frequently than we might expect which may limit the usefulness of the panel aspect of the data for some applications

GfK Panel Data Analysis of meat consumption

This short report represents a summary of the analysis conducted so far on the GfK Panel Data. The focus was on the main three types of raw meat: chicken, pork, beef, as well as three categories of processed food products: liver paste, cold cuts and sausages. The aim was to look at the market indicators for each one of the six sub-categories, out of which market share and penetration were considered to be the most important. Besides these two indicators, I also included some extra calculations for each category, which can be analysed further and more in-depth if needed. One of the desired outcomes of the analyses was to identify companies and brands that were successful in each sub-category. Unfortunately, due to the generally low market shares of the organic products, the number of options was limited. Beef and pork were two categories where no brands were registered in the original product and sales Files. In the chicken category there was only one brand registered between 2006 and 2010, however, the market shares were extremely low for this category. There were only one or two households buying organic chicken products. The processed meat sub-categories both had a few companies registered. However, the diversity isn’t large. Still, it is good to notice that in the three sub-categories there were two companies that were most present: Farre Food and Hanegal. Market shares were generally low for all six sub-categories. Organic beef, pork and liver paste were the only categories to reach market shares of over 1%, while organic chicken had the lowest market shares of all. The trends were generally fluctuating over time. The highest market shares for liver paste, pork, chicken and beef were registered in 2007. All these four categories had much lower market shares in 2009, but it is interesting to notice that in the same year, organic cold cuts and sausages registered the highest market shares. Except for chicken, all market shares dropped in 2010 compared to 2009. Penetration levels had a clear descending trend for organic beef and liver paste, whereas for the other subcategories the levels fluctuated. Organic chicken and sausage generally had an ascending trend, while organic pork and cold cuts usually had descending trends in penetration levels. The highest penetration rates were registered in 2006 for liver paste, beef and cold cuts and in 2008 for sausages, chicken and pork. Out of all the six sub-categories that were analysed, organic beef has had the highest market shares and highest penetration rates, even though the figures were lower and lower every year. Regarding the average price paid/100 gr of meat products, we notice that in the organic category there is more fluctuation than in the conventional category, meaning that the price of organic products varies more between years. According to the analysis, the price difference between the organic and the conventional options in a sub-category is clearly notices in the processed meat category, but it is not as well defined for chicken, pork and beef. There are some limitations regarding the analysis of the panel data. On the one hand, these are due to the fact that there are some incompatibilities between the product file and the sales file regarding the identification of products as being organic or not. On the other hand, some of the products were registered as “unknown”, meaning that they are neither analysed as being organic, nor as being conventional, but as being a separate category. It is considered however that due to the fact that the results of the analysis are so small, the correction of these errors would not change the numbers significantly

An analysis of consumer panel data

In terms of collecting comprehensive panel expenditure data, there are trade-offs to be made in terms of the demands imposed on respondents and the level of detail and spending coverage collected. Existing comprehensive spending data tends to be cross-sectional whilst panel studies include only limited expenditure questions that record spending only as broad aggregates. More recently, economists have begun to use spending information collected by market research companies that records very detailed spending down to the barcode level from a panel of households, usually recorded by in-home barcode scanners, which may provide considerable advantages over existing data more commonly used in social sciences. However, there has not been a comprehensive assessment of the strengths and weaknesses of this kind of data collection method and the potential implications of survey mode on the recorded data. This paper seeks to address this, by an in-depth examination of scanner data from one company, Taylor Nelson Sofres (TNS), on grocery purchases over a five-year period. We assess how far the ongoing demands of participation inherent in this kind of survey lead to 'fatigue' in respondents' recording of their spending and compare the demographic representativeness of the data to the well-established Expenditure and Food Survey (EFS), constructing weights for the TNS that account for observed demographic differences. We also look at demographic transitions, comparing the panel aspect of the TNS to the British Household Panel Study (BHPS). We examine in detail the expenditure data in the TNS and EFS surveys and discuss the implications of this method of data collection for survey attrition. Broadly, we suggest that problems of fatigue and attrition may not be so severe as may be expected, though there are some differences in expenditure levels (and to some extent patterns of spending) that cannot be attributed to demographic or time differences in the two surveys alone and may be suggestive of survey mode effects. Demographic transitions appear to occur less frequently than we might expect which may limit the usefulness of the panel aspect of the data for some applications.Household panel data, scanner data, expenditure, food, duration models, attrition

Portuguese tourism demand:a dynamic panel data analysis

This article considers the determinants of Portuguese tourism demand for the period 2004-2013. The econometric methodology uses a panel unit root test and the dynamic panel data (GMM-system estimator). The different techniques of panel unit root (Levin, Lin and Chu; Im, Pesaran and Shin W-stat and augmented Dickey-Fuller - Fisher Chi-square) show that the variables used in this panel are stationary. The dynamic model proves that tourism demand is a dynamic process. The variables relative prices, income per capita, human capital and government spending encourage international tourism demand for Portugal.info:eu-repo/semantics/publishedVersio

Endogenous contagion – a panel data analysis

This paper proposes a panel data model to analyze contagion in a multivariate framework. The model distinguishes between vulnerability and contagion, and provides a time series of contagion. The most important feature of the model is the endogenous determination of contagion without an a priori and potentially arbitrary specification of the crisis period. In addition, the model can distinguish between positive and negative contagion, and no assumption needs to be made about the source of the crisis. Eleven stock markets from the Asian region are analyzed during the Asian financial crisis, and contagion is found to be significant in four broad periods. These episodes are split equally between positive and negative movements. Anecdotal evidence is matched to the significant incidences of contagion, and it is found that events surrounding Hong Kong equity markets are key drivers of contagion

Drivers of Fund Performance: A Panel Data Analysis

The principle aim of this research is to elucidate the factors driving the total rate of return of non-listed funds using a panel data analytical framework. In line with previous results, we find that core funds exhibit lower yet more stable returns than value-added and, in particular, opportunistic funds, both cross-sectionally and over time. After taking into account overall market exposure, as measured by weighted market returns, the excess returns of value-added and opportunity funds are likely to stem from: high leverage, high exposure to development, active asset management and investment in specialized property sectors. A random effects estimation of the panel data model largely confirms the findings obtained from the fixed effects model. Again, the country and sector property effect shows the strongest significance in explaining total returns. The stock market variable is negative which hints at switching effects between competing asset classes. For opportunity funds, on average, the returns attributable to gearing are three times higher than those for value added funds and over five times higher than for core funds. Overall, there is relatively strong evidence indicating that country and sector allocation, style, gearing and fund size combinations impact on the performance of unlisted real estate funds.unlisted real estate funds, performance analysis, commercial real estate, panel data analysis

The shadow economy Kuznets’s curve panel data analysis

The review of recent literature shows the relationship between shadow economy and economic growth is ambiguous. This paper attempts to answer whether the relationship between shadow economy and economic growth depends on the level of development or not? In this way, the Shadow Economy Kuznets’s Curve (SEKC) is estimated in two quadratic -Inverted U- and cubic -N shape- functional form by using shadow economies data of 21 selected OECD countries for time period of 1995-2006. The panel data analyses results show that cubic functional form justifies the relationship between shadow economy and economic growth better, this relationship depends on the level of development and the shadow economy has a positive effect on the official economy.Shadow economy, economic growth, Kuznets’s curve, panel data analysis, OECD

Effectiveness of Competition Law: A Panel Data Analysis

The paper explores what macroeconomic factors can tell us about the effectiveness of recently enacted national competition laws. Qualitative evidence suggests that numerous countries fall short in implementing competition law. Furthermore, there seems to be significant differences between countries. To examine what factors might contribute to the explanation of effectiveness of competition law panel regression analysis is used. The results indicate that the level of economic development matters, however the institutional learning curve is also relevant. Furthermore, larger countries should be more concerned with competition advocacy activities than smaller countries and it seems to be the case that the problem of capture of competition law is serious in countries with high levels of corruption.competition law enforcement, developing and transition countries