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This paper provides an alternative approach to penalized regression for model selection in the context of high‐dimensional linear regressions where the number of covariates is large, often much larger than the number of available observations. We consider the statistical significance of individual covariates one at a time, while taking full account of the multiple testing nature of the inferential problem involved. We refer to the proposed method as One Covariate at a Time Multiple Testing (OCMT) procedure, and use ideas from the multiple testing literature to control the probability of selecting the approximating model, the false positive rate, and the false discovery rate. OCMT is easy to interpret, relates to classical statistical analysis, is valid under general assumptions, is faster to compute, and performs well in small samples. The usefulness of OCMT is also illustrated by an empirical application to forecasting U.S. output growth and inflation. [ABSTRACT FROM AUTHOR]

A stochastic framework for coordination of macroeconomic policies is introduced in this paper. It is suggested that: (i) measures of policy accountability should allow for the climate of uncertainty that surrounds policy decisions, and (ii) most models of aggregate economic activity impose arbitrary specifications of uncertainty that do not appear to be empirically justifiable. Ambiguities in interpreting the Humphrey-Hawkins reports of policy authorities are sketched in section II; a proposal for maximizing the ex ante prospects of policy objectives is illustrated in section III; finally, nonstationary allocations of uncertainty are discussed in sections IV and V. This paper provides a brief survey of ongoing work by members of the Federal Reserve Board staff on the role of uncertainty in policy forecasts. It suggests that policy discussion could be improved by more explicit consideration of the allocation of uncertainty. [ABSTRACT FROM AUTHOR]

The article comments on a paper published within the issue, "Capital Formation and the Recent Productivity Slowdown," by Peter Clark. The author also discusses results from his own research in "Accounting for United States Economic Growth, 1929-1969," and applies it to Clark's paper. It is suggested that an abrupt rise in energy prices may have affected growth rates during the mid-1970s. The author also looks at a similar analysis made by John Kendrick, who focuses on the U.S. postwar period of 1948-1966.

Estimating the contribution of enslaved workers to output and growth in the United States during the first half of the nineteenth century is a crucial building block to better understand the contours of nineteenth‐century US economic history, and more generally, the connection between slavery and capitalism. Existing estimates only present a partial picture and are potentially problematic. In this paper, we use data on enslaved person valuations to calculate the contribution made by enslaved workers to regional and national gross national product (GNP) in 1839 and 1859 and to the growth in per capita output in the 20 years before the Civil War. We find that in the United States, enslaved workers were responsible for somewhere between 12.49 per cent and 18.0 per cent of the increase in output per capita between 1839 and 1859. [ABSTRACT FROM AUTHOR]

Abstract: The high level of debt among households outside the top end of the income distribution has led many economists to assert that household debt has been an important component of the increase in income inequality in the United States. In addition, the yield spread provides information about the overall condition of the economy and may also be tied into the distribution of income. The paper's results show that increases in the yield spread and household debt correspond with increases in top income shares, resulting in increases in income inequality. However, as household debt and income inequality increase, the yield spread contracts, which suggests future economic contraction. Thus, rising inequality may signal future economic weakness. [ABSTRACT FROM AUTHOR]

The article comments on three papers within the issue: "Long-Term Effects of Government Deficits on the U.S. Output Potential," by George von Furstenburg, "Capital Formation and the Recent Productivity Slowdown," by Peter Clark, and "U.S. Productivity Growth Recession: History and Prospects for the Future," by Michael McCarthy. The author discusses each article and criticizes their shortcomings. He looks at von Furstenburg's use of the Phelps-Shell model of dynamic economic growth and notes the usefulness of neoclassical growth theory. The author feels that his discussion on the effects of government deficits on output growth or productivity represent a fruitful economic analysis innovation.

Summary: This paper describes a weekly economic index (WEI) developed to track the rapid economic developments associated with the onset of and policy response to the novel coronavirus in the United States. The WEI is a weekly composite index of real economic activity, with eight of 10 series available the Thursday after the end of the reference week. In addition to being a weekly real activity index, the WEI has strong predictive power for output measures and provided an accurate nowcast of current‐quarter GDP growth in the first half of 2020, with weaker performance in the second half. We document how the WEI responded to key events and data releases during the first 10 months of the pandemic. [ABSTRACT FROM AUTHOR]

Despite economic growth since the recession, the gap between the richest and the poorest segments of the population remains one of the most pressing concerns of contemporary America. This paper uses IR-95/20, IR-80/20, and IR-65/35 ratios to measure the income divides between the richest and the poorest segments in the mid-to-large-sized metropolises of the U.S. Southeast, their variation across ethnicities, and their association with metropolitan level attributes such as diversity, segregation, socio-economic, and other built-environment, and labor characteristics. The income divide ratios serve as the dependent variables whereas principal components along with state-dummy variables serve as the explanatory variables in regressions analyses. The metropolises that are large, diverse, and better educated are the most income-divided whereas those with lower educated people are less divided. Metropolises with larger shares of their labor engaged in primary sectors of economy have higher income divides; this observation also holds true for African Americans and Hispanics. Metropolises that gained in intermixing during 2000-2014 are associated with a lower income divide and vice versa. [ABSTRACT FROM AUTHOR]

Between 1957 and 1990, nearly 100 nuclear reactors were constructed throughout the U.S., and nuclear power currently accounts for 20 percent of electricity production nationwide. Nuclear plants are often constructed in small communities for which they constitute a large source of employment and income. To date, 24 nuclear reactors have undergone decommissioning, and more are expected in the future, particularly as nuclear reactors age and face increasingly strict regulations. This paper examines the effects of nuclear decommissioning over time at the county-level on measures of employment, income, and population using difference-in-differences regression and propensity score matching. Panel data are obtained from the U.S. Census Bureau, and cover the years 1975-2014. The analysis finds that nuclear decommissioning is associated with positive and statistically significant increases in employment and per capita income over time. Results suggest that nuclear decommissioning may actually be a positive force in regional economic development, and concludes with limitations of the approach and implications for future research. As an emerging area of research, this paper is meant to build on previous work, as well as to provide a basis for further discussion and debate on the economic future of nuclear host communities and regional economies. [ABSTRACT FROM AUTHOR]

This paper estimates the medium‐ to long‐run effects of slavery in the United States in a spatial regression discontinuity design. Using the boundary between free and slave states immediately antebellum, we find that legal slavery decreased per capita manufacturing output by as much as 30% in the decades following the Civil War. Perhaps surprisingly, agricultural output and farm values were only briefly depressed in former slave states after the war. Although emancipation ended slavery, political forces kept the institution from being completely disintegrated, and we explore channels through which this was possible. We show that slavery affected the structure of the economy in a given region—specifically through agricultural production decisions—and that these structures persisted long after passage of the 13th Amendment. However, sharecropping played a relatively small role in this region. Our results support mounting evidence in recent literature of the significant and lasting effects of institutions on economic development. [ABSTRACT FROM AUTHOR]

In the last year, a central issue in regional economic growth debate has been represented by the empirical analysis of Verdoorn's law related to the long-term dynamic relationship between the rate of growth in output and the productivity growth due to increasing returns. Several papers have tested Verdoorn's law on European countries as well as many other world economies. Recently, attempts have been made to provide foundations for a spatial version of the original law specification. The main contributions were dedicated to the inclusion of spatial dependence in the economic model. Surprisingly, in the literature on Verdoom's law the analysis of the spatial heterogeneity is not often considered. The aim of this paper is the regional analysis of the spatial dependence and heterogeneity in Verdoorn's law, identifying spatial regimes that can be interpreted as clusters of productivity growth in European regions at NUTS 2 level. To pursue this objective, an optimization algorithm for the identification of groups is used. This constitutes a modified version of Simulated Annealing. [ABSTRACT FROM AUTHOR]

As science becomes increasingly cross‐disciplinary and scientific models become increasingly cross‐coupled, standardized practices of model evaluation are more important than ever. For normally distributed data, mean squared error (MSE) is ideal as an objective measure of model performance, but it gives little insight into what aspects of model performance are "good" or "bad." This apparent weakness has led to a myriad of specialized error metrics, which are sometimes aggregated to form a composite score. Such scores are inherently subjective, however, and while their components may be interpretable, the composite itself is not. We contend that, a better approach to model benchmarking and interpretation is to decompose MSE into interpretable components. To demonstrate the versatility of this approach, we outline some fundamental types of decomposition and apply them to predictions at 1,021 streamgages across the conterminous United States from three streamflow models. Through this demonstration, we hope to show that each component in a decomposition represents a distinct concept, like "season" or "variability," and that simple decompositions can be combined to represent more complex concepts, like "seasonal variability," creating an expressive language through which to interrogate models and data. Plain Language Summary: Models are essential scientific tools for explaining and predicting phenomena ranging from weather and climate, to health outcomes, to economic development, to the origins of the universe, and testing competing models is one of the most basic scientific activites. Yet, how scientists evaluate and justify their models can be inconsistent or even arbitrary. Traditionally, one performance metric—such as mean squared error—is used to identify the best model, but one metric provides little insight into what aspects of a model are "good" or "bad." This paper proposes a basic language for expressing different aspects of a model's performance. On one hand, this is useful for determining which aspects of model may require revision, but it also allows the modeler to separate out the best elements among several models and combine them to form an ensemble, analogous to how an audio engineer mixes together multiple tracks to form the best rendition of a musical piece. Key Points: Mean squared error (MSE) is an objective but somewhat enigmatic measure of model performanceMSE can be decomposed into components that quantify specific aspects of model performance, such as bias and varianceMixing components among models yields a form of ensemble prediction [ABSTRACT FROM AUTHOR]

Before 2007/08, the European Monetary Union (EMU) was expected to be enlarged on schedule, but the European sovereign debt problem, triggered by the exogenous US sub-prime crisis, not only has revealed the EMU's fiscal coordination failure, but also has weakened regional financial integration. The stagnation of financial integration will therefore increase the cost of sustaining a monetary union, which in turn slows EMU enlargement and ruins the reputation of the euro. This paper aims to measure the damage to financial integration and to provide a more precise answer on real interest rate parity (RIP) convergence. Our estimation indicates that RIP between the EMU and some accession candidates is still valid after the interruptions of the financial crises. However, convergence of real interest rates cannot be achieved until 2030. This implies the EMU authority must strengthen regional financial integration to solidify the EMU and then be able to re-start enlargement. [ABSTRACT FROM AUTHOR]

Understanding the nature of structural change and the sources of economic growth of an economy, especially the relative importance of different industries, is essential for policy-making. This paper estimates industry contribution to economic growth in both Canada and the United States. It argues that industry contribution should be evaluated on the basis of the performance of an industry in terms of creating economic value relative to other industries. In particular, it calls for the quantity and the price effects, which is consistent with real GDP in the chained-Fisher index that values the industry more when its price rises and less when its price declines. This is an important departure from the traditional methodologies that consider only quantity effect. This paper shows that the contribution from demand-driven industries is significantly more than the finding based on traditional thinking. [ABSTRACT FROM AUTHOR]

Natural resource dependence, although commonly invoked in natural resource sociology, has often been ambiguously defined. Communities are frequently described as dependent on natural resource development, but limited attention has been paid to what that means. In the literature, resource dependence is often treated as over‐specialization in, or over‐reliance upon, the natural resource sectors. However, the logic of over‐specialization conceptually grounds dependence in poor economic outcomes. Thus, a one‐dimensional typology of dependence based on a threshold of the share of development in the natural resource sector—as commonly used—does not fully capture the concept and risks tautology. In this paper, I address this ambiguity by formally defining natural resource dependence as over‐specialization in the natural resource sectors. I then present an ideal typology, known as the Natural Resource Community Typology, and a corresponding classification scheme for rural communities in the United States. The typology integrates both extractive and non‐extractive natural resource activity and has two dimensions—the level of development and the level of economic prosperity—and six mutually exclusive categories—extractive specialized, extractive dependent, non‐extractive specialized, non‐extractive dependent, hybrid specialized, and hybrid dependent. I classify counties from 2000 to 2015 and find that while extractive dependence decreased over the study period, non‐extractive dependence increased. [ABSTRACT FROM AUTHOR]

Policymakers across the Southern U.S. have directed considerable attention to regional economic development plans, with mixed results. Questions remain over what types of industries, firms, and/or policies can drive long-range growth. Over the past two decades, researchers have started to focus on high-growth firms (HGFs) due to their potential innovation spillovers and job creation prospects, both of which drive further economic development. Employing databases from the Inc. 500, this study explores the dynamics of HGFs within Southern and comparative contexts. The first goal of this paper is to explore Southern HGF activity in comparison with the U.S. at-large. The second is to examine the geographical characteristics of HGFs within the South, which will include an exploration of locations, industrial mix, and the factors that could encourage HGF development and agglomeration. This paper will also analyze the longer-term ownership and acquisition patterns of HGFs across the South. Are such firms remaining embedded in the South or moving elsewhere through mergers or acquisitions? The paper concludes with a discussion of the impacts of HGFs on regional economic development and moreover, whether existing policies are conducive to these firms. [ABSTRACT FROM AUTHOR]

Copyright of Canadian Journal of Economics is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper studies the patterns of government expenditure stimuli among Organisation for Economic Co-operation and Development ( OECD) countries during the Great Recession (2007-2009). Overall, we find that the USA net fiscal stimulus was modest relative to peers, despite it being the epicenter of the crisis, and having access to relatively cheap funding of its twin deficits. Of the 28 countries in the sample, the USA is ranked among the bottom third in terms of the rate of expansion of consolidated government consumption and investment expenditures. Contrary to historical experience, emerging markets had strongly countercyclical policy during the period immediately preceding the Great Recession and the Great Recession itself. Federal unions, emerging markets and countries with very high gross domestic product ( GDP) growth during the pre-recession period saw larger net fiscal stimulus on average than their counterparts. We also find that greater net fiscal stimulus was associated with lower flow costs of general government debt in the same or subsequent period. [ABSTRACT FROM AUTHOR]

Copyright of Regional Science Policy & Practice is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

For more than five decades, the federal, state, and local governments have subsidized mass transit systems through sales, gasoline, and property taxes with an expectation that it would improve mobility to low-income citizens, reduce carbon footprints and traffic congestion, and facilitate regional economic growth. However, in times of financial crisis and chronic government budget deficits, the inefficient use of a mass transit system can increase public outcry over the wasteful spending of government funds and taxpayers' monies. To find ways to utilize mass transit systems more efficiently across the United States, this paper aimed to identify the benchmark transit practices that every mass transit system can emulate and then continuously improve its performance. To achieve these goals, this paper analyzed the multiple years of past performances of 262 mass transit agencies in the United States using data envelopment analysis and the Malmquist productivity index and then provided practical guidelines for enhancing mass transit efficiency. [ABSTRACT FROM AUTHOR]