Real exchange rate persistence and the excess return puzzle: The case of Switzerland versus the US

The PPP puzzle refers to the wide swings of nominal exchange rates around their long‐run equilibrium values whereas the excess return puzzle represents the persistent deviation of the domestic‐foreign interest rate differential from the expected change in the nominal exchange rate. Using the I(2) cointegrated VAR model, much of the excess return puzzle disappears when an uncertainty premium in the foreign exchange market, proxied by the persistent PPP gap, is introduced. Self‐reinforcing feedback mechanisms seem to cause the persistence in the Swiss‐US parity conditions. These results support imperfect knowledge based expectations rather than so‐called “rational expectations”.     

Refining Stylized Facts from Factor Models of Inflation

Factor models of disaggregate inflation indices suggest that sectoral shocks generate the bulk of sectoral inflation variance, but no persistence. Aggregate shocks, by contrast, are the root of sectoral inflation persistence, but have negligible relative variance. We show that simple factor models do not cope well with essential features of price data. In particular, sectoral inflation series are subject to features such as measurement error, sales and item substitutions. In factor models, these blow up the variance of sector‐specific shocks, while reducing their persistence. We control for such effects by estimating a refined factor model and find that inflation variance is driven by both aggregate and sectoral shocks. Sectoral shocks, too, generate substantial inflation persistence. Both findings contrast with earlier evidence from factor models, but align well with recent micro evidence. Our results have implications for the foundations of price stickiness, and provide quantitative inputs for calibrating models with sectoral heterogeneity. Copyright © 2014 John Wiley & Sons, Ltd.     

Estimating the intergenerational persistence of lifetime earnings with life course matching: Evidence from the PSID

Why do estimates of the intergenerational persistence in earnings vary so much for the United States? Recent research suggests that lifecycle bias may be a major factor [Grawe, N., Lifecycle bias in estimates of intergenerational earnings persistence. Labour Economics 2006, 13:551–570; Haider, S., and Solon, G., Life-cycle variation in the association between current and lifetime earnings. American Economic Review 2006, 96(4):1308–1320.]. In this paper we estimate the intergenerational correlation in lifetime earnings by using sons' and fathers' earnings at similar ages in order to account for lifecycle bias. Our estimate based on earnings measured at 35–44 for both fathers and sons is similar to that for the age range 45–54.     

Analysis of regional productivity with capital as a quasi-fixed factor

Most existing studies of regional productivity growth do not incorporate the effect of variations in capacity utilization on changes in output. By failing to do so, their factor productivity estimates are biased. To overcome this shortcoming, we adjust multifactor productivity growth measure for changes in capacity utilization. Our technique recognizes that capital is a quasi-fixed factor which implies that capital in the short run can be either under- or over-utilized by a firm. Our results from 1974 to 1978 show that capacity adjusted multifactor productivity growth measure exceeds capacity unadjusted multifactor productivity growth measure for the nine census divisions. The bias in the capacity unadjusted measure of multifactor productivity growth is approximately 8 percent in East North Central and over 33 percent in Mountain. We find that the aggregate factor productivity growth is slowest in the traditional manufacturing belt (Middle Atlantic and East North Central divisions). The level of aggregate factor productivity in the manufacturing belt, however, is almost 33 percent higher than in regions in the south.     

Disaggregate productivity comparisons: sectoral convergence in OECD countries

International comparisons of productivity have used exchange rates or purchasing power parity (PPP) to make output comparable across countries. While aggregate PPP holds well in the long run, sectoral deviations are persistent. It raises the need for a currency conversion factor at the same level of aggregation as the output that is compared. Mapping prices from household expenditure surveys into the industrial classification of sectors and adjusting for taxes and international trade, I obtain an expenditure-based sector-specific PPP. Using detailed price data for up to 8 years between 1970 and 1999, I test whether the sectoral PPPs adequately capture differential changes in relative prices between countries. They work well for agriculture and the majority of industrial sectors, but not for most service sectors and for manufacturing sectors that produce differentiated products. Using the most appropriate conversion factor for each industry, productivity convergence is found to be taking place in all but a few industries for a group of 14 OECD countries. The latter results are robust to the base year used for the currency conversion.     

Fractional integration in daily stock market indices at Jordan's Amman stock exchange

Using daily data on five sectoral indices from 2006 to 2014, this paper aims to investigate the possibility of fractional integration in sectoral returns (and their volatility measures) at Jordan's Amman stock exchange (ASE). Empirical analysis, using the log-periodogram (LP) and local whittle (LW) based semi-parametric fractional differencing techniques suggest that all sectoral returns at ASE exhibit short memory. However, in the case of volatility measures, we found evidence of long memory. Following the recent literature that argues that structural breaks in a time series could also explain the presence of long memory, we tested the volatility measures for the presence of structural breaks. We found that long memory in some volatility measures could be attributed to the presence of structural breaks. Furthermore, using impulse response functions (IRF) based on ARFIMA, we found that shocks to sectoral returns at ASE exhibit short run persistence, whereas shocks to volatility measures display long run persistence.     

Understanding the Fisher equation

It is argued that univariate long memory estimates based on ex post data tend to underestimate the persistence of ex ante variables (and, hence, that of the ex post variables themselves) because of the presence of unanticipated shocks whose short‐run volatility masks the degree of long‐range dependence in the data. Empirical estimates of long‐range dependence in the Fisher equation are shown to manifest this problem and lead to an apparent imbalance in the memory characteristics of the variables in the Fisher equation. Evidence in support of this typical underestimation is provided by results obtained with inflation forecast survey data and by direct calculation of the finite sample biases. To address the problem of bias, the paper introduces a bivariate exact Whittle (BEW) estimator that explicitly allows for the presence of short memory noise in the data. The new procedure enhances the empirical capacity to separate low‐frequency behaviour from high‐frequency fluctuations, and it produces estimates of long‐range dependence that are much less biased when there is noise contaminated data. Empirical estimates from the BEW method suggest that the three Fisher variables are integrated of the same order, with memory parameter in the range (0.75, 1). Since the integration orders are balanced, the ex ante real rate has the same degree of persistence as expected inflation, thereby furnishing evidence against the existence of a (fractional) cointegrating relation among the Fisher variables and, correspondingly, showing little support for a long‐run form of Fisher hypothesis. Copyright © 2004 John Wiley & Sons, Ltd.     

The Zero Lower Bound and Parameter Bias in an Estimated DSGE Model

This paper examines how and to what extent parameter estimates can be biased in a dynamic stochastic general equilibrium (DSGE) model that omits the zero lower bound (ZLB) constraint on the nominal interest rate. Our Monte Carlo experiments using a standard sticky‐price DSGE model show that no significant bias is detected in parameter estimates and that the estimated impulse response functions are quite similar to the true ones. However, as the frequency of being at the ZLB or the duration of ZLB spells increases, the parameter bias becomes larger and therefore leads to substantial differences between the estimated and true impulse responses. It is also demonstrated that the model missing the ZLB causes biased estimates of structural shocks even with the virtually unbiased parameters. Copyright © 2015 John Wiley & Sons, Ltd.     

Estimates of technical inefficiency in stochastic frontier models with panel data: generalized panel jackknife estimation

Estimates of technical inefficiency based on fixed effects estimation of the stochastic frontier model with panel data are biased upward. Previous work has attempted to correct this bias using the bootstrap, but in simulations the bootstrap corrects only part of the bias. The usual panel jackknife is based on the assumption that the bias is of order T ⁻¹ and is similar to the bootstrap. We show that when there is a tie or a near tie for the best firm, the bias is of order T ^−1/2, not T ⁻¹, and this calls for a different form of the jackknife. The generalized panel jackknife is quite successful in removing the bias. However, the resulting estimates have a large variance.     

On solving bias‐corrected non‐linear estimation equations with an application to the dynamic linear model

In a seminal paper, Mak, Journal of the Royal Statistical Society B, 55, 1993, 945, derived an efficient algorithm for solving non‐linear unbiased estimation equations. In this paper, we show that when Mak's algorithm is applied to biased estimation equations, it results in the estimates that would come from solving a bias‐corrected estimation equation, making it a consistent estimator if regularity conditions hold. In addition, the properties that Mak established for his algorithm also apply in the case of biased estimation equations but for estimates from the bias‐corrected equations. The marginal likelihood estimator is obtained when the approach is applied to both maximum likelihood and least squares estimation of the covariance matrix parameters in the general linear regression model. The new approach results in two new estimators when applied to the profile and marginal likelihood functions for estimating the lagged dependent variable coefficient in the dynamic linear regression model. Monte Carlo simulation results show the new approach leads to a better estimator when applied to the standard profile likelihood. It is therefore recommended for situations in which standard estimators are known to be biased.     

On the Importance of Sectoral and Regional Shocks for Price‐Setting

We use novel disaggregate sectoral‐regional euro‐area data to investigate the sources of price changes, introducing a new method to extract factors from overlapping data blocks that allows for estimation of aggregate, sectoral, country‐specific and regional components of price changes. Our sectoral component explains much less variation in disaggregate inflation rates and exhibits much less volatility and more persistence than previous findings for the US indicate. Country‐ and region‐specific factors play an important role, emphasizing heterogeneity of inflation dynamics along both sectoral and geographical dimensions. Our results are incompatible with basic sticky‐information or Calvo‐type price‐setting models, but require multi‐sector, multi‐country models. Copyright © 2015 John Wiley & Sons, Ltd.     

Disaggregate evidence on the persistence of consumer price inflation

This paper uses disaggregate inflation data spanning all of consumption to examine: (i) the persistence of disaggregate inflation relative to aggregate inflation; (ii) the distribution of persistence across consumption sectors; and (iii) whether persistence has changed. Assuming mean inflation to be unchanged, disaggregate persistence inflation is consistently below aggregate persistence. Taking into account an early 1990s shift in mean inflation identified by break tests yields much lower estimates of both aggregate and disaggregate persistence for 1984–2002. But with the mean break, average disaggregate persistence is actually as great as aggregate inflation persistence. A factor model provides a natural framework for interpreting the relationship between aggregate and disaggregate persistence. Copyright © 2006 John Wiley & Sons, Ltd.     

Secondary products and the measurement of productivity growth

The paper considers alternative treatments of secondary products in input-output systems and analyzes their implications for the measurement of productivity growth at both the sectoral and overall level. Two standard models of secondary products are used: (1) the commodity technology model and (2) the industry technology model. It is argued that the first model correctly relates sectoral and overall levels of productivity growth; the second model, though more conventional, aggregates sectoral levels to a biased estimate of overall productivity growth. Estimates of the two measures are provided using U.S. 85-sector input-output data for 1967, 1972, and 1977. The empirical results indicate that the alternative assumptions do not lead to significantly different estimates of commodity-level and industry-level productivity growth over this period for the full economy but do for several sectors. Moreover, changes in secondary production did not contribute significantly to the decline in productivity growth over this period but secondary production was found to have a much lower rate of productivity growth than primary production.     

Temporal aggregation of an ESTAR process: some implications for purchasing power parity adjustment

Nonlinear models of deviations from PPP have recently provided an important, theoretically well motivated, contribution to the PPP puzzle. Most of these studies use temporally aggregated data to empirically estimate the nonlinear models. As noted by Taylor ( 2001 ), if the true DGP is nonlinear, the temporally aggregated data could exhibit misleading properties regarding the adjustment speeds. We examine the effects of different levels of temporal aggregation on estimates of ESTAR models of real exchange rates. Copyright © 2006 John Wiley & Sons, Ltd.     

Threshold bipower variation and the impact of jumps on volatility forecasting

This study reconsiders the role of jumps for volatility forecasting by showing that jumps have a positive and mostly significant impact on future volatility. This result becomes apparent once volatility is separated into its continuous and discontinuous components using estimators which are not only consistent, but also scarcely plagued by small sample bias. With the aim of achieving this, we introduce the concept of threshold bipower variation, which is based on the joint use of bipower variation and threshold estimation. We show that its generalization (threshold multipower variation) admits a feasible central limit theorem in the presence of jumps and provides less biased estimates, with respect to the standard multipower variation, of the continuous quadratic variation in finite samples. We further provide a new test for jump detection which has substantially more power than tests based on multipower variation. Empirical analysis (on the S&P500 index, individual stocks and US bond yields) shows that the proposed techniques improve significantly the accuracy of volatility forecasts especially in periods following the occurrence of a jump.     

Estimating the economic return to educational levels using data on twins

This paper relaxes some restrictions of previous twin‐based estimates of the effects of education on earnings. First, it estimates the earnings premiums associated with different educational levels. Second, it estimates a piecewise linear relationship between the natural logarithm of annual earnings and years of schooling. Third, the measurement error corrections are based on a less restrictive, ‘non‐classical’, measurement error model. The estimation strategy implies that ability bias can be investigated separately in different parts of the educational distribution. The linear relationship between the logarithm of annual earnings and years of schooling is rejected. Furthermore, the results in the sample of identical (MZ) twins indicated both that the ability bias could be of different signs and of different magnitudes in different parts of the educational distribution. The twin‐based estimates in the sample of fraternal (DZ) twins did not display any marked differences as compared to the cross‐sectional estimates. Finally, the results indicated that the error‐corrected twin‐based estimates of the average return to years of schooling that rely on a classical measurement error model are upwards biased by approximately 30%. Copyright © 2004 John Wiley & Sons, Ltd.     

Does unemployment hysteresis falsify the natural rate hypothesis? a meta‐regression analysis

Abstract.  A quantitative survey of 24 studies containing 99 national estimates of unemployment persistence reinstates unemployment hysteresis as a viable falsifying hypothesis to the natural rate hypothesis. Empirical evidence to the contrary may be attributed to small-sample, misspecification and publication biases. Larger estimates of unemployment persistence are produced by models that use more information ( t  = 9.03; P  < 0.0001) and are better specified. A theme of bias and misspecification among studies that are more supportive of natural rate hypothesis emerges in several independent ways. The nonstationarity of the unemployment rate is confirmed both by the observed rate of convergence of persistence estimates across the empirical literature and by the point towards which they converge. The natural rate hypothesis may be regarded as 'falsified' should we choose to do so.     

Non-separability and sectoral comovement in a sticky price model

This paper resolves the sectoral comovement problem between nondurable and durable outputs that arises in response to a monetary shock in a two-sector sticky price model with flexibly priced durable goods. We analytically demonstrate that the non-separability between aggregate consumption and labor can generate the comovement between nondurable and durable outputs in response to a monetary policy shock. We then estimate the degree of non-separability, together with other parameters, using a Bayesian approach. We find that the non-separable preferences are supported by the data and our estimated model generates the sectoral comovement in response to a monetary shock.     

Estimates of the return to schooling in Sweden from a large sample of twins

A large sample of twins was used to examine whether conventional estimates of the return to schooling in Sweden are biased because ability is omitted from the earnings–schooling relationship. Ignoring measurement error, the results indicate that omitting ability from the earnings–schooling relationship leads to estimates that are positively biased. However, reasonable estimates of the measurement-error-adjusted returns are both above and below the unadjusted estimates, showing that the results depend crucially on a parameter not known at this time. However, an estimate of the reliability ratio was obtained using two measures on educational attainment. With this estimate of the reliability ratio, the measurement-error-adjusted estimate of the return to schooling in the sample of identical twins indicates that there is at most a slight ability bias in the conventional estimates of the return to schooling. The fundamental assumption of this kind of study is that within-pair differences in educational attainment are randomly determined. This assumption was also tested, but no strong evidence to reject it was found.     

On the need to compensate the compensating variation in CGE modeling

The message of this research is that in the standard calibrated setting of Computational General Equilibrium (CGE) models, the welfare measures typically used to compare benchmark with counterfactuals are numéraire dependent. This evaluation bias affects the compensating variation and the Konüs index of cost of living. We show that the equivalent variation is neutral regarding the choice of value units in calibrated models but would be affected as well in uncalibrated CGE models. We illustrate with a simple example and propose an even simpler theoretical solution to overcome these biases; all that is required to have correct welfare estimates is to compensate normalizing with a suitable price index. This type of correction is necessary to overcome the sometimes blind implementation of welfare measures in numerical general equilibrium analysis. We show that the induced quantitative errors may be substantial providing biased welfare estimates and misleading results.