Improving the CPI’s Age-Bias Adjustment: Leverage, Disaggregation and Model Averaging

As a rental unit ages, its quality typically falls; a failure to correct for this would result in downward bias in the CPI. We investigate the BLS age bias imputation and explore two potential categories of error: approximations related to the construction of the age bias factor, and model mis-specification. We find that, as long as one stays within the context of the current official regression specification, the approximation errors are innocuous. On the other hand, we find that the official regression specification – which is more or less of the form commonly used in the hedonic rent literature – is severely deficient in its ability to match the conditional log-rent vs. age relationship in the data, and performs poorly in out-of-sample tests. It is straightforward to improve the specification in order to address these deficiencies. However, basing estimates upon a single regression model is risky. Age-bias adjustment inherently suffers from a general problem facing some types of hedonic-based adjustments, which is related to model uncertainty. In particular, age-bias adjustment relies upon specific coefficient estimates, but there is no guarantee that the true marginal influence of a regressor is being estimated in any given model, since one cannot guarantee that the Gauss-Markov conditions hold. To address this problem, we advocate the use of model averaging, which is a method that minimizes downside risks related to model misspecification and generates more reliable coefficient estimates. Thus, after selecting several appropriate models, we estimate age-bias factors by taking a trimmed average over the factors derived from each model. We argue that similar methods may be readily implemented by statistical agencies (even very small ones) with little additional effort. We find that, in 2004 data, BLS age-bias factors were too small, on average, by nearly 40%. Since the age bias term itself is rather small, the implied downward-bias of the aggregate indexes is modest. On the other hand, errors in particular metropolitan areas were much larger, with annual downward-bias as large as 0.6%.Depreciation, Hedonics, Model Averaging, Inflation, CPI Bias

Phagocytosis of Streptococcus pyogenes by all-trans retinoic acid-differentiated HL-60 cells: roles of azurophilic granules and NADPH oxidase.

BACKGROUND: New experimental approaches to the study of the neutrophil phagosome and bacterial killing prompted a reassessment of the usefulness of all-trans retinoic acid (ATRA)-differentiated HL-60 cells as a neutrophil model. HL-60 cells are special in that they possess azurophilic granules while lacking the specific granules with their associated oxidase components. The resulting inability to mount an effective intracellular respiratory burst makes these cells more dependent on other mechanisms when killing internalized bacteria. METHODOLOGY/PRINCIPAL FINDINGS: In this work phagocytosis and phagosome-related responses of ATRA-differentiated HL-60 cells were compared to those earlier described in human neutrophils. We show that intracellular survival of wild-type S. pyogenes bacteria in HL-60 cells is accompanied by inhibition of azurophilic granule-phagosome fusion. A mutant S. pyogenes bacterium, deficient in M-protein expression, is, on the other hand, rapidly killed in phagosomes that avidly fuse with azurophilic granules. CONCLUSIONS/SIGNIFICANCE: The current data extend our previous findings by showing that a system lacking in oxidase involvement also indicates a link between inhibition of azurophilic granule fusion and the intraphagosomal fate of S. pyogenes bacteria. We propose that differentiated HL-60 cells can be a useful tool to study certain aspects of neutrophil phagosome maturation, such as azurophilic granule fusion

The long-run relationship between house prices and rents

I show that when house prices are high relative to rents (that is, when the rent-price ratio is low) changes in real rents tend to be larger than usual and changes in real prices tend to be smaller than usual. Standard error-correction models provide inconclusive results about the predictive power of the rent-price ratio at a quarterly frequency. I use a long-horizon regression approach to show that the rent-price ratio helps predict changes in real rents and real prices over three-year periods. This result withstands the inclusion of a measure of the user cost of capital. I show that a long- horizon regression approach can yield biased estimates of the degree of error correction if prices have a unit root but do not follow a random walk. I construct bootstrap distributions to conduct appropriate inference in the presence of this bias. The results lend empirical support to the view that the rent-price ratio is an indicator of valuation in the housing market.Housing - Prices ; Rental housing - Prices

The long-run relationship between house prices and income: evidence from local housing markets

The proposition that "housing prices can't continue to outpace growth in household income" (Wall Street Journal; July 25, 2002) is the received wisdom among many housing-market observers. More formally, many in the housing literature argue that house prices and income are cointegrated. In this paper, I show that the data do not support this view. Standard tests using 27 years of national-level data do not find evidence of cointegration. However, it is known that tests for cointegration have low power, especially in small samples. I use panel-data tests for cointegration that have been shown to be more powerful than their standard time-series counterparts to test for cointegration in a panel of 95 metro areas over 23 years. Using a bootstrap approach to allow for cross-correlations in city-level house-price shocks, I show that even these more powerful tests do not reject the hypothesis of no cointegration. Thus the error-correction specification for house prices and income commonly found in the literature may be inappropriate.Housing ; Housing - Prices

Net migration and state labor market dynamics

I present a simple model of migration in which the net migration rate into a state depends on the expected present value of labor market conditions and amenities. I show that though this is a common model, existing empirical estimates do not separately identify the underlying parameters. The identification problem can be thought of as an omitted variable bias because no explicit measure of expected future labor market conditions is included. I use state-level data to estimate empirical models in which the underlying parameters are identified. I find that high wages and low unemployment encourage in-migration, but that the omitted variable bias can be large. For example, when I control for future conditions in one model, the strength of the relationship between current wages and net migration is less than half as large. I integrate the migration model into a simple labor supply and demand framework and use my estimates of the migration model to simulate a labor market's response to permanent and transitory demand shocks. In the short run, net migration responds more to permanent shocks and current wages and employment rates respond more to transitory ones.Emigration and immigration ; Labor market