Monthly Archives: July 2014

INFORMATION PROVISION: Coefficient of Variation

Posted by Kathryn Schwartz on July 31, 2014
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R&Rs significantly reduce price dispersion for infant and toddler care. Thus, we find that controlling for socio-demographics and market characteristics reverses the pattern observed in the raw data. The table below summarizes predicted effects along with standard errors, for markets with and without R&Rs. The presence of R&Rs reduces price dispersion by 75%, from 0.317 to 0.081, in markets for infant care, and it reduces price dispersion by 52%, from 0.313 to 0.150, in markets for toddler care. These findings are statistically significant and are consistent with the predicted effects of information provision. Moreover, they may be interpreted as evidence that parents of infants and toddlers who do value quality care highly are willing to bear greater search costs than parents who value child care quality less.
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INFORMATION PROVISION: Price Distributions 2

Posted by Kathryn Schwartz on July 29, 2014
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The coefficient of primary interest is that associated with RANDR. Recall from Section 3 that for the dispersion of prices to decrease with increased information, one of two conditions had to hold. Either parents who value quality highly are wealdy more inclined to keep searching until they obtain a good match than are parents who have lower valuations of quality or parents who value quality in child care less must be more inclined to either drop out of the market or stay at the first provider they encounter.
Similarly, reduced form equations for maximum price and average price are specified as:
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INFORMATION PROVISION: Price Distributions

Posted by Kathryn Schwartz on July 27, 2014
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Recall that the model outlined in Section 3, provides predictions for the effect of search costs on the dispersion of prices, the maximum price in the market and the average price in the market. Calculation of the average and maximum prices is straightforward. We use the coefficient of variation as our measure of price dispersion. This is a commonly used measure of the relative dispersion of different distributions that does not vary with units of measurement. Table 3 presents summary statistics for each price distribution (PINFANT, PTODDLER, PPRESCH, PSCHOOL).
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INFORMATION PROVISION: Explanatory Variables 2

Posted by Kathryn Schwartz on July 25, 2014
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To specify the vector of regulatory variables included in the model we draw on previous work by Chipty & Witte (1994), Chipty (1995) and Chipty & Witte (1997). Specifically, we control for the following center regulations: whether liability insurance is required (INSURE), whether pre or in-servicing training is required for the staff (TRAIN), the minimum square feet of indoor space required per child (SQFEET), the maximum group size (GRSZ) by age, and the minimum staff-child ratio (SCRAT) by age.

Since center behavior was found to be affected by the nature of regulations for family child care homes as well as by center regulations, we also control for the regulations imposed on family child care homes. Specifically, we control for the following family child care home regulations: maximum group size (FGRSZ) allowed, and whether pre or in-service training is required (FTRAIN). Finally, to reflect enforcement of regulations we include the number of inspections required per year for centers (INSPECT) and family child care homes (FINSPECT).

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INFORMATION PROVISION: Explanatory Variables

Posted by Kathryn Schwartz on July 23, 2014
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Using the group level data, we also construct average staff-child ratio (ASCRATI, ASCRATT, ASCRATPS, and ASCRATS, for infants, toddlers, preschoolers, and school-age, respectively). Table 1 (a) presents descriptive statistics for the price and staff/child ratio variables at the center level and Table 2 and 3 presents descriptives at the market-level.
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INFORMATION PROVISION: Market Definition 2

Posted by Kathryn Schwartz on July 21, 2014
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Determinants of Observed Price and Quality Distributions
To structure our empirical work, we adopt a model of supply and demand for child care developed by Chipty and Witte (1994). For the purposes of this paper, we estimate the reduced form implied by this model. The estimation of a carefully specified reduced form increases our confidence in results we obtain for the effect of R&Rs on the distribution of prices.
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INFORMATION PROVISION: Market Definition

Posted by Kathryn Schwartz on July 19, 2014
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As described in Section 2, the quality and price of child care varies markedly from provider to provider and parents often incur substantial search costs to obtain the care they want for their children. Over half of the counties in our sample are served by a R&R, providing a centralized source of information on the price, quality and location of child care providers. Our model indicates generally that markets with R&Rs should have prices that are less disperse than markets without R&Rs. If parents who highly value quality care have greater willingness to search than parents with lower valuations for child care quality, then markets with R&Rs may also have lower maximum and average prices. To empirically determine the effect of R&Rs on the distribution of equilibrium market prices, we need to define child care markets and we need to specify an empirical model that incorporates other determinants of observed price distributions.
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INFORMATION PROVISION: Equilibrium with Perfect Information 3

Posted by Kathryn Schwartz on July 17, 2014
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After some algebra, we have the following proposition:
Proposition 3 If xH >ь ’ imperfect information results in increased price dispersion, higher maximum price, and higher average price.

In order for search costs to raise average market price, the increase in the high quality firm’s price must be large enough to more than offset the decrease in the low quality firm’s price. The high quality firm’s price can only increase by enough if high valuation consumers are willing to search substantially more than lower valuation consumers. Indeed, high valuation consumers have be more than twice as willing to search as low valuation consumers in order for average prices to fall. It is straightforward to prove that if the condition for Proposition 3 is satisfied, so are the conditions for Propositions 1 and 2.
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INFORMATION PROVISION: Equilibrium with Perfect Information 2

Posted by Kathryn Schwartz on July 15, 2014
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When xH 2: xu the high quality firm has a higher expected demand when information is imperfect than when there is full information. Under imperfect information, the high quality firm continues to serve all high valuation consumer in the interval [A, 1], as it did under perfect information. Now, this firm will also serve some lower valuation consumers, in the interval [AH, A], who happen to find the high quality firm first (see Figure 1). The low quality firm has a lower expected demand when information is imperfect.
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INFORMATION PROVISION: Equilibrium with Perfect Information

Posted by Kathryn Schwartz on July 13, 2014
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Next consider the situation where consumers costlessly observe the price and quality of the product offered by each firm prior to making their purchases. Given the firms’ price-quality combinations ( As before, to solve for the Nash equilibrium in prices, we derive market shares for each firm. The marginal consumer who is indifferent between qH at price pH and qL at price pL is given P by: 0 = -2L_L = A . Similarly, the marginal consumer who is indifferent between purchasing qL and making no purchase has a valuation of: 6 = — . Thus, the market share for the high quality firm is 1 – A
Each firm chooses price to maximize profits, which are found by multiplying price-cost margins by market share. Equilibrium prices are given by:

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