Timing and Quantity of Consumer Purchases--论文代写范文精选

  这篇essay代写范文的分析表明,普通消费者在选择上是更为重要的。此外,消费行为的数据显示，显著的异质性与人口有关。忽略时间和数量因素,计算价格指数时,可能会产生一定误差，下面的essay代写范文进行阐述。

Abstract 
A common approach to measuring price changes is to look at the change of the expenditure needed to purchase a fixed basket of goods. It is well-known that this approach suffers from problems and creates several biases in the measurement of price changes faced by consumers. Substitution and outlet bias, two commonly studied concerns, are both driven by consumer choices of what and where to buy. However, consumers also make other choices, including how much and when to buy. We discuss the implications of consumers’ timing and quantity decisions have on standard practices of computing a price index. We use household-level data on quantities purchased and prices paid to construct a measure of the savings made by consumers’ optimizing behaviour in the purchase of food. In particular, we compare the prices actually paid by the consumers to various alternatives that do not allow for substitution. Our analysis suggests that the average consumer makes significant, and comparable in magnitude, savings from the four dimensions of choice that we study. Furthermore, our data suggests significant heterogeneity in consumer behavior, and that this behavior is correlated with demographics. Our findings suggest that ignoring timing and quantity decisions, when computing a price index, can generate biases on the order of magnitude of substitution and outlet biases.

Introduction 
One of the major challenges faced by applied economists is the measurement of price changes. The middle part of 2008 saw significant increases in the prices of food, vehicle fuel and household energy, for example. How do we measure how much prices have increased? In practice, the most common approach to measuring prices changes is to look at the changes of the expenditure needed to purchase a fixed basket of goods. This approach dates back at least to the early nineteenth century (Diewert, 1993), and has a large number of variations. It is well-known that this approach suffers from problems and creates several biases in the measurement of price changes faced by consumers.2 

Common concerns include substitution bias, outlet bias, quality change, treatment of new products, and heterogeneity across consumers. Substitution and outlet bias, two commonly studied concerns, are both driven by consumer choices of what and where to buy. However, consumers also make other choices, including how much and when to buy. Many products are sold at non-linear prices: the price per unit, say an ounce, is typically lower for larger pack sizes. Thus, a consumer has a choice of not just what product to buy and where to buy it, but also what size to buy (and what price to pay). Similarly, many products have temporary price reductions – sales – that allow the consumer to purchase more today and potentially stockpile for future consumption. Both these dimensions of choice have been mentioned as potential sources of bias in price indices (e.g., Feenstra and Shapiro, 2003; Triplett, 2003; and references therein), but are discussed less often than the first two biases.

The standard approach to price measurement does not properly account for the fact that consumers do not face a single price, but rather face a distribution of prices (Baye, 1985; Reinsdorf, 1994). The variation in prices can be across goods, stores, size and over time. Different consumers will react to this variation differently, depending on their preferences and costs. For example, some consumers might have lower travel costs and therefore be more likely to shop at a range of different stores. Other consumers might have lower storage and transport costs and will therefore take greater advantage of quantity discounts and temporary price reductions. Accurate description of price changes has to move beyond the “average” consumer, and explore heterogeneity across consumers (Pollak, 1998). If the relative price of different goods remains fairly constant, there is probably little variation in inflation across households and so distributional issues are not so important. 

In periods of high inflation, and in particular when inflation is driven by only certain commodities, heterogeneity across households is likely to be more important. For example, Deaton and Muellbauer (1980, Table 7.1) report that during 1975-76, when inflation in the UK was 15 percent, the rate for the poor was two points higher than for the rich.3 In this paper we contribute to the literature on the empirical relevance of these issues. We use household-level data on quantities purchased and prices paid to construct a measure of the savings made by consumers’ optimizing behaviour in the purchase of food. We examine the savings made by consumers timing their purchases to buy on sale, buying larger package sizes, buying generic brands or switching between alternative outlets. Furthermore, we document how this behaviour, and the implied savings, varies by demographics including income, family size, and employment status.

We observe data, collected by a marketing firm, on all food purchases brought into the home for a large, nationally representative, sample of UK households in 2006. Compared to previous studies, our data is more comprehensive – not limited to a subsample of goods – and more detailed regarding the brand, package size, location, whether on sale and time of purchase. For each purchase we know exactly what was bought (as measured by the bar code), the price paid and quantity purchased, the purchase date and the store it was purchased in. We also observe household demographics. Using these data, we are able to compare the prices actually paid by the consumers in the sample to various alternatives. （essay代写)

For example, to measure the savings from the timing of purchases we can compare the actual expenditure to the expenditure of a consumer who purchases the same bundle (in terms of products and outlets), but did not buy when the item was on sale. We show how the savings vary with income, age and employment status, as well as other demographics. Our analysis suggests that the average consumer makes significant, and comparable in magnitude, savings from the four dimensions of choice that we study. This demonstrates, on a larger scale, the savings associated with consumer behaviour, found by previous work (e.g., Hendel and Nevo, 2006a, for saving from timing purchases, and Hausman and Leibtag, 2007, for saving from the availability of Wal-Mart). Furthermore, our data suggests significant heterogeneity in consumer behaviour. For example, some households buy a significant fraction of their food on sale, others rarely do. This behaviour is correlated with demographics. In the next section we describe the data that we use and present some preliminary descriptive statistics. In section 3 we consider the potential and actual savings that households make by buying on sale, larger pack sizes, generic brands and in specific stores. In section 4 we compare the levels of savings and a final section makes some concluding remarks.（essay代写)

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