Ross McKitrick

The econometric critique of computable general equilibrium modeling: the role of functional forms

Abstract Computable general equilibrium (CGE) models are among the most influential tools in applied economics. However, some serious questions have been raised about the empirical validity of these models. The core of the critique is that the parameter selection criteria are unsound and the use of first-order (CES class) functional forms imposes influential restrictions on the models structure. A formal summary of the case against standard CGE modeling is presented, as is an alternative econometric-based modeling strategy which answers the critique. We then present a comparative CGE modeling experiment designed to assess the role of function forms. It is found that choice of functional forms affects not only industry-specific results, but aggregate results as well, even for small policy shocks.

Corrections to the Mann et. al. (1998) Proxy Data Base and Northern Hemispheric Average Temperature Series

The data set of proxies of past climate used in Mann, Bradley and Hughes (1998, “MBH98” hereafter) for the estimation of temperatures from 1400 to 1980 contains collation errors, unjustifiable truncation or extrapolation of source data, obsolete data, geographical location errors, incorrect calculation of principal components and other quality control defects. We detail these errors and defects. We then apply MBH98 methodology to the construction of a Northern Hemisphere average temperature index for the 1400–1980 period, using corrected and updated source data. The major finding is that the values in the early 15th century exceed any values in the 20th century. The particular “hockey stick” shape derived in the MBH98 proxy construction – a temperature index that decreases slightly between the early 15th century and early 20th century and then increases dramatically up to 1980 — is primarily an artefact of poor data handling, obsolete data and incorrect calculation of principal components.

Comparing Capital Mobility Across Provincial and National Borders

The persistence of high savings-investment correlations and home-country bias in portfolio construction at the national level is contrasted with new evidence of savings behaviour in Canadian provinces. We confirm that national borders clearly divert flows of capital to domestic investments, but provincial borders have no such effect. In particular, while there is a significant correlation between national savings and investment, among provinces that effect disappears. We discuss the implications for interpreting the distinction between provincial and national borders.

The M&M Critique of the MBH98 Northern Hemisphere Climate Index: Update and Implications

The differences between the results of McIntyre and McKitrick [2003] and Mann et al. [1998] can be reconciled by only two series: The Gaspé cedar ring width series and the first principal component (PC1) from the North American tree ring network. We show that in each case MBH98 methodology differed from what was stated in print and the differences resulted in lower early 15th century index values. In the case of the North American PC1, MBH98 modified the PC algorithm so that the calculation was no longer centered, but claimed that the calculation was “conventional”. The modification caused the PC1 to be dominated by a subset of bristlecone pine ring width series which are widely doubted to be reliable temperature proxies. In the case of the Gaspé cedars, MBH98 did not use archived data, but made an extrapolation, unique within the corpus of over 350 series, and misrepresented the start date of the series. The recent Corrigendum by Mann et al. denied that these differences between the stated methods and actual methods have any effect, a claim we show is false. We also refute the various arguments by Mann et al. purporting to salvage their reconstruction, including their claims of robustness and statistical skill. Finally, we comment on several policy issues arising from this controversy: the lack of consistent requirements for disclosure of data and methods in paleoclimate journals, and the need to recognize the limitations of journal peer review as a quality control standard when scientific studies are used for public policy.

Does a Global Temperature Exist

Abstract Physical, mathematical, and observational grounds are employed to show that there is no physically meaningful global temperature for the Earth in the context of the issue of global warming. While it is always possible to construct statistics for any given set of local temperature data, an infinite range of such statistics is mathematically permissible if physical principles provide no explicit basis for choosing among them. Distinct and equally valid statistical rules can and do show opposite trends when applied to the results of computations from physical models and real data in the atmosphere. A given temperature field can be interpreted as both “warming” and “cooling” simultaneously, making the concept of warming in the context of the issue of global warming physically ill-posed.

Reply to comment by Huybers on “Hockey sticks, principal components, and spurious significance”

[1] McIntyre and McKitrick [2005a] (hereinafter referred to as MM05) showed that the actual Mann et al. [1998] (hereinafter referred to as MBH98) PC method used an unreported short-centering method, which was biased towards producing a hockey stick shaped PC1 with an inflated eigenvalue. Huybers [2005] concurs with these particular findings, but argues that we ‘‘exaggerated’’ the MBH98 bias by comparing the MBH98 PC1 for the North American tree ring network to a covariance PC1 rather than a correlation PC1 by MM05 (Figure 3). [2] Tree ring chronologies (both density and ring width) are already standardized to common dimensionless units with a mean of 1. Huybers’ [2005] two statistical authorities either do not recommend standardizing variance for PC analysis on series with common units [Preisendorfer, 1988] or recommend the opposite (i.e., a covariance PC calculation) [Rencher, 1995, p. 430; see also Overland and Preisendorfer, 1982; Rencher, 1992]. Only Rencher [1995] even mentions the possibility of standardizing variance of networks in common units in exceptional circumstances that do not apply here. [3] One of Huybers’ [2005] principal justifications for proposing a correlation PC1 is his observation that the covariance PC1 underweights density series, which have lower variances. But in the MBH98 network, only 2 of 70 series are density series, and both are from sites also represented in the same network with a ring width series. Indeed, the Spruce Canyon site (density series co509x and ring width series co509w) also occurs in 4 series in the MBH98 Stahle/SWM network. Accommodating these 2 density series should not be at the expense of the most appropriate treatment for the other 68. [4] Relative to the MBH98 PC1, the differences between the covariance PC1 and correlation PC1 are trifling and both confirm the bias reported in MM05. The MBH98 method applied to North American tree rings had the distinctive hockey stick shape (Figure 1a) and a very large first eigenvalue (38%), which they interpreted as evidence of a ‘‘dominant component of variance’’. Neither the covariance PC1 (Figure 1c) nor the correlation PC1 (Figure 1e) have a hockey stick shape and their first eigenvalue is much reduced (19%, 17% respectively). The correlation PC1 is a little higher in the 20th century than the covariance PC1, but the differences are trifling. [5] Huybers’ [2005] approach also ignores fundamental properties of the data and introduces new and unconsidered biases: [6] a) Tree ring chronologies are typically autocorrelated, especially the controversial bristlecones. For autocorrelated series, the ordinary least squares sample variance (used by Huybers) is a biased (under-) estimate of the long-run variance, so the bristlecones will tend to be over-weighted this way. An ‘‘unbiased fully normalized’’ PC1 can be obtained using an autocorrelation-consistent variance estimator [e.g., Andrews, 1991]. This bias correction yields a result (Figure 1g) very similar to the covariance PC1. [7] b) Huybers argues that the correlation PC1 captured a ‘‘robust feature of the NOAMER dataset’’ based on its similarity to the mean of the 70 series in the AD1400 network scaled by their standard deviation (Figure 1f). If the purpose of PC analysis is merely to predict the mean, then there is no reason not to simply use the mean. As for the robustness of the feature, only 70 of 212 series in the NOAMER network extend back to AD1400. Using all 212 NOAMER series scaled by their standard deviation (Figure 1d) yields a network mean closer to the covariance PC1 than the correlation PC1—by this criterion ‘‘full normalization’’ adds bias to the PC1. [8] The differences among these PC series can be traced to differing weights for bristlecones. Bristlecone sites are well-known examples of CO2 fertilization and their nonclimatic biases have been extensively assessed already—see the caveat by Intergovernmental Penal on Climate Change [1996] and the review by McIntyre and McKitrick [2005b]. Huybers [2005] is correct to acknowledge the need to assess their validity and possibly to exclude or down-weight them, but having said so it is inadequate to defer this to ‘‘future studies.’’ We see no sense deferring to the future a remedy for what is already a well-understood source of bias. [9] Bristlecone impact can be seen directly by comparing the MBH98 PC1 (Figure 1a), which is weighted almost entirely from bristlecones, with an unreported PC1 from Mann’s FTP site (Figure 1b), which Mann obtained by GEOPHYSICAL RESEARCH LETTERS, VOL. 32, L20713, doi:10.1029/2005GL023586, 2005

Double Dividend Environmental Taxation and Canadian Carbon Emissions Control

The possibility of using revenues from environmental taxes to reduce other distortions in the tax system (the so-called double dividend approach) has been discussed recently. This paper reviews the current debate and presents empirical evidence to suggest that the double dividend approach can significantly reduce the cost of CO2 emissions control in Canada and possibly eliminate aggregate welfare and output reductions due to implementation of a carbon tax.

A Cournot Mechanism for Pollution Control under Asymmetric Information

The contribution of this paper is to show that a simple nonlinear tax can achieve a long-run socially optimal level of pollution without the regulator knowing marginal abatement costs. Firms are charged their differential contribution to total damages, evaluated at the upper margin of current emissions. This induces a Cournot game in pollution levels. We show that the Nash equilibrium exists, corresponds to the socially optimal long-run output and emission levels and number of firms, is stable, and can be reached by iterative computations where conjectures are formed using a linear estimator based on past emission levels.

Socioeconomic patterns in climate data

Summary To generate a climate data set, temperature data collected at the Earth’s surface must be adjusted to remove non-climatic effects such as urbanization and measurement discontinuities. Some studies have shown that the post-1980 spatial pattern of temperature trends over land in prominent climate data sets is strongly correlated with the spatial pattern of socioeconomic development, implying that the adjustments are inadequate, leaving a residual warm bias. This evidence has been disputed on three grounds: spatial autocorrelation of the temperature field undermines significance of test results; counterfactual experiments using model-generated data suggest such correlations have an innocuous interpretation; and different satellite covariates yield unstable results. Somewhat surprisingly, these claims have not been put into a coherent framework for the purpose of statistical testing. We combine economic and climatological data sets from various teams with trend estimates from global climate models and we use spatial regressions to test the competing hypotheses. Overall we find that the evidence for contamination of climatic data is robust across numerous data sets, it is not undermined by controlling for spatial autocorrelation, and the patterns are not explained by climate models. Consequently we conclude that important data products used for the analysis of climate change over global land surfaces may be contaminated with socioeconomic patterns related to urbanization and other socioeconomic processes. Research Supported by Social Sciences and Humanities Research Council of Canada Grant Number 430002

Proxy inconsistency and other problems in millennial paleoclimate reconstructions

Mann et al. (1) present two paleoclimate reconstruction methods [“error-in-variables” (EIV) and “composite plus scale” (CPS)], claiming statistically significant skill for both. Their figure 3 reveals that from approximately 750 to 1100, the CPS 95% confidence interval excludes the EIV 95% confidence interval and vice versa. This is evidence not of skill, but of inconsistency.