Abstract
In a recent contribution, Nikiforos (Nikiforos, M. 2016. On the utilisation controversy: a theoretical and empirical discussion of the Kaleckian model of growth and distribution, Cambridge ...Journal of Economics, vol. 40, no. 2, 437–67) has claimed that the FED data on capacity utilisation are stationary by construction, and thus, not suitable to test the Neo-Kaleckian model. He then proceeds to provide new series on capital utilisation, which he claims are non-stationary and provide, supposedly, support for the Neo-Kaleckian model. This comment presents two interrelated claims. First, the measurement error that Nikiforos claims to be I(1) in the FED series is I(0), and what is measured with error is only the level of the series. Thus, this series is suitable to test the Neo-Kaleckian model. Secondly, he does not provide unit root tests for the series he suggests as superior to the FED. When this exercise is carried out, almost all unit root tests decidedly reject the existence of a stochastic trend on his three proposed series, which, according to the author, do not lend support to the Neo-Kaleckian model. We conclude that measures of capacity utilisation based on FRB data are a reasonable source to test the implications of a wide variety of macroeconomic models.
In this paper, we analyze the relationship between energy intensity and energy price in a panel of 120 countries over 34 years, from 1980 to 2013. We use information on energy intensity and real oil ...price, and merge it with macroeconomic data on the countries' structural characteristics. We assess their long-run relationship and direction of causality using panel cointegration tests and dynamic panel data models. We identify a statistically significant, but weak negative effect of real oil price on energy intensity, which corresponds to a positive effect of energy price on energy efficiency. We also show significant, large regional differences in this relationship. We thus posit that a global policy aimed at increasing the price of oil would induce a limited increase in average energy efficiency through a more efficient use of energy, but this increase would differ considerably across regions around the world.
Abstract
We estimate the importance of inherited wealth in Sweden over the past 200 years. Inheritance is measured both as the annual inheritance flow divided by national income and as the share of ...inherited wealth in all private wealth. In the 19th century, Sweden differs from France and the United Kingdom in having much lower inheritance–income flows, but at the same time exhibiting equally large shares of inherited wealth in total wealth. This pattern is in line with Sweden at the time being a poor country with low domestic capital accumulation, but at the same time exhibiting high economic growth rates. In the 20th century the importance of inheritance in relation to national income fell, but since the 1990s it has increased rapidly, today reaching almost the same levels as a century ago. The share of inherited wealth in total wealth has also fallen over time, but remains relatively low due to a rapid accumulation of new wealth. We study potential determinants and explanations, pointing especially to Swedish welfare-state institutions, and in particular to the development of an extensive public occupational pension system contributing to keeping private inheritance low.
Forecasting macroeconomic risks Adams, Patrick A.; Adrian, Tobias; Boyarchenko, Nina ...
International journal of forecasting,
07/2021, Letnik:
37, Številka:
3
Journal Article
Recenzirano
Odprti dostop
We construct risks around consensus forecasts of real GDP growth, unemployment, and inflation. We find that risks are time-varying, asymmetric, and partly predictable. Tight financial conditions ...forecast downside growth risk, upside unemployment risk, and increased uncertainty around the inflation forecast. Growth vulnerability arises as the conditional mean and conditional variance of GDP growth are negatively correlated: downside risks are driven by lower mean and higher variance when financial conditions tighten. Similarly, employment vulnerability arises as the conditional mean and conditional variance of unemployment are positively correlated, with tighter financial conditions corresponding to higher forecasted unemployment and higher variance around the consensus forecast.
This paper calculates the carbon footprint of private consumption in the EU27 by five groups of household income, using a fully fledged macroeconomic input-output model covering 59 industries and ...five groups of household income for the EU27. Due to macroeconomic feedback mechanisms, this methodology – besides induced intermediate demand – also quantifies: (i) private consumption induced in the other household groups, (ii) impacts on other endogenous final demand components, and (iii) negative feedback effects due to output price effects of household demand. The carbon footprint is calculated separately for the consumption vector of each of the five income groups. The simulation results yield a non-linear income elasticity of direct and indirect emissions at each income level: the value of the direct footprint income elasticity decreases from 1.32 (first quintile) to 0.69 (fourth quintile). The value of the indirect footprint income elasticity is always below unity and decreases from 0.89 to 0.62. The results in general reveal a relative decoupling effect: the share of the top income group in income (45%) is much larger than its share in the carbon footprint (37%) and vice versa for the bottom income group (6% in income and 8% in footprint).
The relative performances of forecasting models change over time. This empirical observation raises two questions. First, is the relative performance itself predictable? Second, if so, can it be ...exploited in order to improve the forecast accuracy? We address these questions by evaluating the predictive abilities of a wide range of economic variables for two key US macroeconomic aggregates, namely industrial production and inflation, relative to simple benchmarks. We find that business cycle indicators, financial conditions, uncertainty and measures of past relative performances are generally useful for explaining the models’ relative forecasting performances. In addition, we conduct a pseudo-real-time forecasting exercise, where we use the information about the conditional performance for model selection and model averaging. The newly proposed strategies deliver sizable improvements over competitive benchmark models and commonly-used combination schemes. The gains are larger when model selection and averaging are based on both financial conditions and past performances measured at the forecast origin date.
The effects of oil price fluctuations on growth, inflation, and exchange rates for Indonesia are investigated in the framework of the structural vector autoregressive (SVAR). To identify linking oil ...prices to the macroeconomic activities accurately, the entire sample period is separated into two sub-samples such as the era of net oil exporter (1998:M1-2003:M12) and the era of net oil importer (2004:M1-2019:M4). In the era of net oil exporter, we discover that a surge in oil prices promotes growth and contributes to appreciating the Indonesian currency. In the era of net oil importer, by contrast, an upsurge in oil prices reduces growth and causes a depreciation of the exchange rate. However, there is little evidence that an upswing in oil prices in both eras has a significantly detrimental effect on inflation.
The national accounts provide a coherent and exhaustive description of the current state of the economy, but are available at the quarterly frequency and are released with a nonignorable publication ...lag. The paper illustrates a method for nowcasting and forecasting the sixteen main components of Gross Domestic Product (GDP) by output and expenditure type at the monthly frequency, using a high-dimensional set of monthly economic indicators spanning the space of the common macroeconomic and financial factors. The projection on the common space is carried out by combining the individual nowcasts and forecasts arising from all possible bivariate models of the unobserved monthly GDP component and the observed monthly indicator. We discuss several pooling strategies and we select the one showing the best predictive performance according to a pseudo-real-time forecasting experiment. Monthly GDP can be indirectly estimated by the contemporaneous aggregation of the value added of the different industries and of the expenditure components. This enables the comparative assessment of the indirect nowcasts and forecasts vis-à-vis the direct approach and a growth accounting exercise. Our approach meets the challenges posed by the dimensionality, since it can handle a large number of time series with a complexity that increases linearly with the cross-sectional dimension, while retaining the essential heterogeneity of the information about the macroeconomy. An application to the Italian case leads to several interesting discoveries concerning the time-varying predictive content of the information carried by the monthly indicators.
Summary
This paper illustrates how to handle a sequence of extreme observations—such as those recorded during the COVID‐19 pandemic—when estimating a vector autoregression, which is the most popular ...time‐series model in macroeconomics. Our results show that the ad hoc strategy of dropping these observations may be acceptable for the purpose of parameter estimation. However, disregarding these recent data is inappropriate for forecasting the future evolution of the economy, because it may underestimate uncertainty.
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