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This paper presents a framework for quantifying uncertainty around point forecasts for GDP, inflation and house prices in Norway. The framework combines quantile regressions using a broad set of uncertainty indicators with a skewed t-distribution, allowing for time-variation and asymmetry in the uncertainty forecasts. This approach helps provide deeper insights into the macroeconomic uncertainty surrounding forecasts than more traditional time-series models, where uncertainty is usually symmetric and with limited time-variation. Formal tests, such as the log score and the Continuous Ranked Probability Score (CRPS), show that using informative indicators tend to improve density forecasts, particularity in the medium run.

We propose a novel copula approach to producing density forecasts of economic aggregates combining models using disaggregate data. Our copula approach is more flexible compared to existing techniques, because it is applicable to any econometric model that produces density forecasts. We construct a set of Monte Carlo studies to investigate the properties of the suggested approach. In our empirical application, we use the Norwegian index for goods consumption (VKI) and the Norwegian consumer price index for underlying inflation (CPI-ATE). We find that the copula approach compares well to alternative methods using recursive out-of-sample estimation.

Forecasting and estimating core inflation has recently gained attention, especially for inflation targeting countries, following research showing that targeting headline inflation may not be optimal; a Central Bank can miss the signal due to the noise. Despite its importance there is sparse literature on estimating and forecasting core inflation in South Africa, with the focus still on measuring core inflation. This paper emphasises predicting core inflation using large time-varying parameter vector autoregressive models (TVP-VARs), factor augmented VAR, and structural break models using quarterly data from 1981Q1 to 2013Q4. We use mean squared forecast errors (MSFE) and predictive likelihoods to evaluate the forecasts. In general, we find that (i) small TVP-VARs consistently outperform all other models; (ii) models where the errors are heteroscedastic do better than models with homoscedastic errors; (iii) models assuming that the forgetting factor remains 0.99 throughout the forecast period outperforms models that allow for the forgetting factors to change with time; and (iv) allowing for structural break does not improve the predictability of core inflation. Overall, our results imply that additional information on the growth rate of the economy and interest rate is sufficient to forecast core inflation accurately, but the relationship between these three variables needs to be modelled in a time-varying (nonlinear) fashion.

There is widespread disagreement about the role of housing wealth in explaining consumption. This paper exploits liquid and illiquid wealth time series from household balance sheet data for South Africa, previously constructed by the authors, to explain fluctuations in the ratios of consumption and household debt to income in South Africa, from 1971 to 2005. The paper emphasizes the role of substantial credit liberalization and of wealth, treating credit conditions as a latent variable with key interactions with drivers of consumption and debt. Credit conditions are proxied by a spline function entering jointly estimated consumption, debt and income expectations equations in a 'latent interactive variable equation system' (LIVES). The empirical results corroborate the theory in the paper, confirming that consumption relative to income is driven by credit liberalization, fluctuations in a range of asset values and asset accumulation, uncertainty and income expectations, inter alia. The paper confirms a collateral interpretation of housing wealth on consumption as opposed to a life-cycle interpretation. The paper also throws important light on the monetary policy transmission mechanism in South Africa.

Using a unique dataset of 22.5 million news articles from the Dow Jones Newswires Archive, we perform an in depth real-time out-of-sample forecasting comparison study with one of the most widely used data sets in the newer forecasting literature, namely the FRED-MD dataset. Focusing on U.S. GDP, consumption and investment growth, our results suggest that the news data contains information not captured by the hard economic indicators, and that the news-based data are particularly informative for forecasting consumption developments.

We ask whether a pay-as-you-go financed social security system is welfare improving in an economy with idiosyncratic productivity and aggregate business cycle risk. We show analytically that the whole welfare benefit from joint insurance against both risks is greater than the sum of benefits from insurance against the isolated risk components. One reason is the convexity of the welfare gain in total risk. The other reason is a direct risk interaction which amplifies the utility losses from consumption risk. We proceed with a quantitative evaluation of social security’s welfare effects. We find that introducing an unconditional minimum pension leads to substantial welfare gains in expectation, even net of the welfare losses from crowding out. About 60% of the welfare gains would be missing when simply summing up the isolated benefits.

In response to the COVID-19 health crisis, the French government has imposed drastic lockdown measures for a period of 55 days. This paper provides a quantitative assessment of the economic and environmental impacts of these measures in the short and long term. We use a Computable General Equilibrium model designed to assess environmental and energy policies impacts at the macroeconomic and sectoral levels. We find that the lockdown has led to a significant decrease in economic output of 5% of GDP, but a positive environmental impact with a 6.6% reduction in CO2 emissions in 2020. Both decreases are temporary: economic and environmental indicators return to their baseline trajectory after a few years. CO2 emissions even end up significantly higher after the COVID-19 crisis when we account for persistently low oil prices. We then investigate whether implementing carbon pricing can still yield positive macroeconomic dividends in the post-COVID recovery. We find that implementing ambitious carbon pricing speeds up economic recovery while significantly reducing CO2 emissions. By maintaining high fossil fuel prices, carbon taxation reduces the imports of fossil energy and stimulates energy efficiency investments while the full redistribution of tax proceeds does not hamper the recovery. Electronic supplementary material The online version of this article (10.1007/s10640-020-00488-z) contains supplementary material, which is available to authorized users.

We use a novel data set covering all domestic debit card transactions in physical terminals by Norwegian households, to nowcast quarterly Norwegian household consumption. These card payments data are free of sampling errors and are available weekly without delays, providing a valuable early indicator of household spending. To account for mixed-frequency data, we estimate various mixed-data sampling (MIDAS) regressions using predictors sampled at monthly and weekly frequency. We evaluate both point and density forecasting performance over the sample 2011Q4-2020Q1. Our results show that MIDAS regressions with debit card transactions data improve both point and density forecast accuracy over competitive standard benchmark models that use alternative high-frequency predictors. Finally, we illustrate the benefits of using the card payments data by obtaining a timely and relatively accurate nowcast of the first quarter of 2020, a quarter characterized by heightened uncertainty due to the COVID-19 pandemic.

This paper presents a computable general equilibrium model (CGEM) able to measure the impacts of the affirmative action policy set up in South Africa. In order to decrease inequalities inherited from the former regime, the government encourages firms to employ Historically Disadvantaged Persons (HDP). Through this study, we evaluate the impact of this policy on employment, poverty and inequality. To evaluate impacts on poverty and inequality, we use a CGE Top Down approach. The paper analyses two scenarios; the first one deals with the impact of affirmative action on skilled jobs. The second scenario adds to the previous by including semi skilled workers in the simulation. Both of these scenarios show a deep decrease in unemployment as well as a fall of poverty for each population groups.

(ProQuest: ... denotes formulae omitted.)1. INTRODUCTIONIn his early study, Chow (1985) reported strong evidence in favor of the Permanent Income Hypothesis (PIH) using annual observations in China from 1953 to 1982. Later, Chow (2010) re-evaluated his model for the post-economic reform regime, 1978 to 2006, then provided the same conclusion.1 Using further updated data, Chow (2011) reported weaker but similar supporting evidence for the PIH in China.We believe these findings are not convincing both theoretically and empirically. Under the PIH, optimizing consumers choose a stable path of consumption over their lifetime.2 This implies that those consumers must borrow whenever their realized current income falls below their permanent income. However, in the absence of perfect capital markets, poor consumers may not be able to access to credit markets (Shoji, Aoyagi, Kasahara, Sawada, and Ueyama, 2012), which implies that liquidity constrained consumers may fail to obey the PIH.One may claim that these consumers may still resort to informal credit markets as Guirkinger (2008) points out. We view these possibilities highly improbable in the case of China. For instance, using rural household data, Yuan and Xu (2015) show that the poor in China are severely excluded from not only formal but also informal credit markets. Therefore, it seems difficult to reconcile Chow's proposed indirect evidence of the PIH with such institutional facts about accessibility to credit markets in China.From an empirical point of view, we note that his empirical analysis focuses on the coefficient of the lagged consumption in an autoregressive (AR) model for consumption. Finding that the confidence band of that coefficient includes 1, he suggested that the PIH is consistent with Chinese annual data. However, his statistical inference may not be valid when consumption obeys an integrated process, because the conventional t-test he uses is invalid when consumption obeys an I(1) process.3 Further, his work does not implement any direct statistical tests for the predictability of consumption growth in China.This paper fills this gap by directly investigating the in-sample and the out-of-sample predictability of consumption changes in China as well as the postwar US data for comparison. Our findings suggest that consumption changes are highly predictable, which provides a clear contrast with findings shown in Chow (1985, 2010, 2011).The rest of the paper is organized as follows. Section 2 provides a data description and preliminary test results. In Section 3, we provide our major findings. Section 4 concludes.2 DATA AND PRELIMINARY ANALYSISWe obtained per capita disposable income ( ) and consumption expenditure ( ) data in China from China Statistical Yearbook (2012) following Chow (1985, 2010, 2011). Observations are annual and span from 1978 to 2012. It should be noted that observations prior to 1978 are excluded, because China began their major economic reforms since 1978, and the pre-economic reform regime data are often unreliable. We deflated all observations using the GDP deflator, obtained from the same source. All data are log transformed.The log real per capita disposable income and the log real consumption expenditures of nondurable goods and services in the US are obtained from the Federal Reserve Economic Data (FRED). Observations are quarterly and cover the period from 1952:Q1 to 2011:Q4.We first implement the augmented Dickey-Fuller (ADF) test for these variables. Results are reported in Table 1. The ADF test rejects the null of nonstationarity only for differenced series with an exception of y t in China when time trend is present. Overall, our test results imply that consumption and income are integrated series, which is also consistent with Chow's work.3. EMPIRICAL FINDINGS3.1. In-Sample AnalysisCampbell and Mankiw (1990) test the validity of the PIH in the US by empirically evaluating Hall's (1978) famous claim: Consumption follows a random walk process under the PIH. …

International audience; Kiyotaki and Wright (1989) model has exerted considerable in ‡uence in the monetary search literature. We argue that the model delivers also important insights on a broader range of macroeconomic and development issues. The analysis studies how market frictions and the liquidity of assets a¤ect the distribution of income. Experiments illustrate how the economy adjusts to shocks to assets' returns and to the matching technology. They also deal with long-run transition. An experiment interprets the reversal of fortune hypothesis as a situation in which an economy with a low-return asset takes over a similar economy with a high-return asset.

У статті наведено основні напрямки та структура розвитку промисловості України. Зроблено аналіз деяких показників галузевої структури промисловості. Обґрунтовано роль та необхідність розгляду макроекономічних показників у розрізі економічного розвитку країни. Проаналізовані деякі макроекономічні показники розвитку України. Розглянуто зв’язок галузевої структури промисловості з макроекономічними показниками та виявлено їх вплив. Основою економіки є виробництво, тобто. створення кінцевого економічного продукту. Без виробництва не може бути споживання. Виробництво матеріальних благ і послуг здійснюють такі основні галузі: промисловість, сільське господарство, будівництво, зв’язок, транспорт. Але фундаментом економіки все ж є промисловість, як провідна галузь. Розвиток промисловості впливає на темпи науково-технічного прогресу в усьому народному господарстві. Промисловість - база розширеного відтворення і економічного розвитку країни, її обороноздатності, вона забезпечує громадян країни товарами народного споживання і різного роду послугами, тому необхідно її показники вивчати більш ретельно і особливо у відповідності до галузевої структури країни. Сучасна промисловість відрізняється складністю складу галузей, виробництв і зв’язків між ними. Кожна з галузей і виробництв характеризуються різним ступенем капіталомісткості, трудомісткості, матеріаломісткості, енергоємності, водоємності, наукоємності тощо. Розвиток економічних наук та застосування математичних методів аналізу економічних процесів дозволило визначити ряд фундаментальних показників галузей промисловості, що характеризують економічний стан будь-якої держави. Такі показники отримали назву макроекономічні показники. Чітке розуміння економічної сутності цих показників і їх взаємного впливу один на одного - це основа для розробки політики регулювання економічних процесів в державі, тому дослідження їх складових у залежності від структурної складової промисловості є нагальною задачею науковців у сучасній економічній системі. Це необхідно для впливу на їх поліпшення, що в цілому буде сприяти закріпленню позитивного іміджу країни на світовій арені. The article gives the main directions and structure of the development of industry in Ukraine. An analysis of some indicators of the sectoral structure of the industry is made. The role and necessity of considering macroeconomic indicators in the context of economic development of the country are substantiated. Some macroeconomic indicators of Ukraine's development are analyzed. The connection of the branch structure of the industry with macroeconomic indicators is considered and their influence is revealed. The basis of the economy is production, ie. creation of the final economic product. Without production, there can be no consumption. The production of material goods and services is carried out by the following main branch: industry, agriculture, construction, communications, transport. But the foundation of the economy is still an industry, as a leading branch. The development of industry affects the pace of scientific and technological progress throughout the national economy. The industry is the base of expanded reproduction and economic development of the country, its defense capacity, it provides citizens of the country with consumer goods and various services, therefore it is necessary to study its indicators more carefully and especially in accordance with the sectoral structure of the country. Modern industry is characterized by the complexity of the branches, industries, and connections between them. Each of the branches and industries is characterized by varying degrees of capital intensity, labor intensity, material intensity, energy intensity, environmental capacity, knowledge intensity, etc. The development of economic sciences and the application of mathematical methods for analyzing economic processes allowed to determine the number of fundamental indicators of industries that characterize the economic situation of any state. Such indicators are called macroeconomic indicators. A clear understanding of the economic nature of these indicators and their mutual influence on each other is the basis for developing a policy of regulating economic processes in the state; therefore, the study of their components, depending on the structural component of the industry, is an urgent task of scientists in the modern economic system. It is necessary to influence their improvement, which in general will help to consolidate the positive image of the country on the world stage.

Nous comparons les prévisions de croissance de l'économie française à l'horizon 2020 réalisées entre septembre et début novembre 2018 par 18 organismes (publics et privés, dont l'OFCE). Après avoir augmenté de 2,3 % en 2017, l'activité ralentirait pour l'ensemble des prévision- nistes interrogés à 1,6 % en moyenne en 2018. Il n'y a pas d'accélération prévue à l'horizon de l'exercice de prévision : l'activité progresserait en moyenne de 1,6 % en 2019 et de 1,5 % 2020 (avec 8 instituts sur 12 qui prévoient un ralentissement). Mais les moteurs de la croissance changeraient. En 2017, la croissance avait été tirée par une forte contribution de la demande intérieure hors stocks tandis que le commerce extérieur jouait négativement. L'histoire est toute autre en 2018, le commerce extérieur, par sa contribution positive, contribuerait à compenser partiellement une demande intérieure moins dynamique. En 2019 et 2020, c'est l'inverse. L'accélération de la consommation des ménages permise par l'amélioration des revenus soutiendrait la croissance, tandis que l'investissement resterait solide. L'environnement international serait moindre favorable et les risques sur la croissance, plutôt orientés à la baisse. Si un consensus existe autour de ce scénario central, il masque malgré tout des divergences entre instituts liées notamment aux hypothèses relatives au positionnement de l'économie française dans son cycle, et donc au degré de tensions dans l'économie. Pour tous, l'inflation reste globalement modérée en prévision (entre 1,4 % et 1,9 % en 2020 selon les instituts) mais l'inflation sous-jacente s'accélère, tout en restant inférieure à 2 %, et certains instituts considèrent que des contraintes d'offre existent, notamment sur le marché du travail. Le taux de chômage baisserait de 9,4 % en 2017 à entre 8,1 % pour les plus optimistes à 9,1 % les plus pessimistes en fin de période. La progression des salaires resterait malgré tout contenue sur la période (avec un maximum à 2,6 % en 2020). L'impact positif des réformes passées et en cours sur la croissance du PIB et la compétitivité des entreprises ne ressort pas véritablement des scénarios. La France est sortie de la Procédure de déficit excessif en 2018 et tous les instituts prévoient le respect des règles budgétaires concernant le déficit public, qui resterait en-deçà du seuil des 3 % à l'horizon 2020. Néanmoins, le déficit se dégraderait 2019, du fait de mesures exceptionnelles (remboursement aux entreprises de la taxe sur les dividendes et transformation du CICE en baisses de charges sociales employeurs) et d'une amélioration de la composante conjoncturelle plus limitée qu'en 2017. En 2020, il serait compris entre 2,7 % et 1,6 % du PIB.

Nous comparons les prévisions de croissance de l'économie française à l'horizon 2020 réalisées entre septembre et début novembre 2018 par 18 organismes (publics et privés, dont l'OFCE). Après avoir augmenté de 2,3 % en 2017, l'activité ralentirait pour l'ensemble des prévision- nistes interrogés à 1,6 % en moyenne en 2018. Il n'y a pas d'accélération prévue à l'horizon de l'exercice de prévision : l'activité progresserait en moyenne de 1,6 % en 2019 et de 1,5 % 2020 (avec 8 instituts sur 12 qui prévoient un ralentissement). Mais les moteurs de la croissance changeraient. En 2017, la croissance avait été tirée par une forte contribution de la demande intérieure hors stocks tandis que le commerce extérieur jouait négativement. L'histoire est toute autre en 2018, le commerce extérieur, par sa contribution positive, contribuerait à compenser partiellement une demande intérieure moins dynamique. En 2019 et 2020, c'est l'inverse. L'accélération de la consommation des ménages permise par l'amélioration des revenus soutiendrait la croissance, tandis que l'investissement resterait solide. L'environnement international serait moindre favorable et les risques sur la croissance, plutôt orientés à la baisse. Si un consensus existe autour de ce scénario central, il masque malgré tout des divergences entre instituts liées notamment aux hypothèses relatives au positionnement de l'économie française dans son cycle, et donc au degré de tensions dans l'économie. Pour tous, l'inflation reste globalement modérée en prévision (entre 1,4 % et 1,9 % en 2020 selon les instituts) mais l'inflation sous-jacente s'accélère, tout en restant inférieure à 2 %, et certains instituts considèrent que des contraintes d'offre existent, notamment sur le marché du travail. Le taux de chômage baisserait de 9,4 % en 2017 à entre 8,1 % pour les plus optimistes à 9,1 % les plus pessimistes en fin de période. La progression des salaires resterait malgré tout contenue sur la période (avec un maximum à 2,6 % en 2020). L'impact positif des réformes passées et en cours sur la croissance du PIB et la compétitivité des entreprises ne ressort pas véritablement des scénarios. La France est sortie de la Procédure de déficit excessif en 2018 et tous les instituts prévoient le respect des règles budgétaires concernant le déficit public, qui resterait en-deçà du seuil des 3 % à l'horizon 2020. Néanmoins, le déficit se dégraderait 2019, du fait de mesures exceptionnelles (remboursement aux entreprises de la taxe sur les dividendes et transformation du CICE en baisses de charges sociales employeurs) et d'une amélioration de la composante conjoncturelle plus limitée qu'en 2017. En 2020, il serait compris entre 2,7 % et 1,6 % du PIB.

This study evaluates the economic impact of a shift towards renewable electricity mix in the Netherlands using the neo-Keynesian CGEM ThreeME (Multi-sector Macroeconomic Model for the Evaluation of Environmental and Energy policy). This scenario has been inspired by the Urgenda's report ‘Energy 100% Sustainable in the Netherlands by 2030’, which have been quantified using the Energy Transition Model (ETM) developed by Quintel. Using the output of the ETM regarding the change in the electricity generation shares as input in ThreeME, we derive the impact in terms of key economic variables (GDP, employment, investment, value-added, prices, trade, tax revenue, etc.). We find that transition to renewable energy may have a positive impact on the Dutch economy, creating almost 50 000 new jobs by 2030 and adding almost 1% of gross domestic product. © 2017

Alors que l'INSEE vient de publier une première estimation de la croissance française de 2017 (1,9 %), nous comparons les prévisions pour 2018 et 2019 réalisées par 18 organismes (publics et privés, dont l'OFCE) entre septembre et décembre 2017. Pour tous la reprise semble solidement enclenchée et durable, avec une croissance moyenne prévue de 1,8 % en 2018 puis de 1,7 % en 2019 : les prévisions sont assez proches pour 2018 (1,7 % à 2 %) mais s'étalent de 1,4 % à 2,2 % en 2019 (avec 8 instituts sur 15 qui prévoient un ralentissement). La consommation privée accélérerait un peu (1,6 % en 2018 et 1,7 % en 2019), avec des écarts nets entre instituts. En effet, l'emploi progresserait entre 0,6 et 1,9 % en 2019 et les salaires entre 1,3 % et 2,6 %. Le diagnostic sur les salaires dépend du degré de tensions sur le marché du travail, de l'impact de l'inflation et des gains de productivité et de l'effet de la réforme du marché du travail de 2017 (décentralisation des négociations collectives). L'inflation resterait modérée (1,4 % en 2019). Le taux de chômage baisserait à 8,8 % en moyenne en 2019 mais les prévisions varient entre 8,1 % et 9,2 %. Pour tous les instituts, le déficit public respecterait dès 2017 le seuil de 3 % du PIB. La France pourrait alors sortir de la Procédure de Déficit Excessif en 2018. Le déficit resterait cependant élevé, du fait de mesures exceptionnelles (remboursement aux entreprises de la taxe sur les dividendes récemment invalidée par le Conseil constitutionnel et transformation du CICE en baisses de charges sociales employeurs en 2019).

This paper employs classical bivariate, slab-and-spike variable selection, Bayesian semi-parametric shrinkage, and factor-augmented predictive regression models to forecast US real private residential fixed investment over an out-of-sample period from 1983Q1 to 2005Q4, based on in-sample estimates for 1963Q1–1982Q4. Both large-scale (188 macroeconomic series) and small-scale (20 macroeconomic series) slab-and-spike variable selection, and Bayesian semi-parametric shrinkage, and factor-augmented predictive regressions, as well as 20 bivariate regression models, capture the influence of fundamentals in forecasting residential investment. We evaluate the ex post out-of-sample forecast performance of the 26 models using the relative average mean square error for one-, two-, four-, and eight-quarter-ahead forecasts and test their significance based on the McCracken (2004, J Econom 140:719–752, 2007) mean-square-error F statistic. We find that, on average, the slab-and-spike variable selection and Bayesian semi-parametric shrinkage models with 188 variables provides the best forecasts among all the models. Finally, we use these two models to predict the relevant turning points of the residential investment, via an ex ante forecast exercise from 2006Q1 to 2012Q4. The 188 variable slab-and-spike variable selection and Bayesian semi-parametric shrinkage models perform quite similarly in their accuracy of forecasting the turning points. Our results suggest that economy-wide factors, in addition to specific housing market variables, prove important when forecasting in the real estate market.

This paper puts forward kernel ridge regression as an approach for forecasting with many predictors that are related to the target variable nonlinearly. In kernel ridge regression, the observed predictor variables are mapped nonlinearly into a high-dimensional space, where estimation of the predictive regression model is based on a shrinkage estimator in order to avoid overfitting. We extend the kernel ridge regression methodology to enable its use for economic time series forecasting, by including lags of the dependent variable or other individual variables as predictors, as is typically desired in macroeconomic and financial applications. Both Monte Carlo simulations and an empirical application to various key measures of real economic activity confirm that kernel ridge regression can produce more accurate forecasts than traditional linear and nonlinear methods for dealing with many predictors based on principal components.

In this paper, we investigate whether the two main consumer confidence indicators available for Sweden – that of the National Institute of Economic Research and that of the European Commission – can nowcast Swedish household consumption expenditure. In a simulated out-of sample nowcast exercise, we find that the consumer confidence indicator of the National Institute of Economic Research appears most useful for this purpose. The root mean square error of the nowcast from the model employing this indicator is the lowest of all the studied models which rely on survey data. The nowcasting performance of the model using the consumer confidence indicator of the European Commission is less impressive; while it outperforms the simplest possible benchmark model, its root mean square error is considerably higher than that of the model relying on the consumer confidence indicator of the National Institute of Economic Research. An implication of our findings is that while the European Commission’s survey programme may have been successful in creating a set of harmonised data for the member countries of the European Union, it is not obvious that the harmonised indicators are the most relevant ones for analysis, nowcasting or forecasting in each country.

Summary We study the role of consumer confidence in forecasting real personal consumption expenditure, and contribute to the extant literature in three substantive ways. First, we re-examine existing empirical models of consumption and consumer confidence, not only at the quarterly frequency, but using monthly data as well. Second, we employ real-time data in addition to commonly used revised vintages. Third, we investigate the role of consumer confidence in a rich information context. We produce forecasts of consumption expenditures with and without consumer confidence measures using a dynamic factor model and a large, real-time, jagged-edge dataset. In a robust way, we establish the important role of confidence surveys in improving the accuracy of consumption forecasts, manifesting primarily through the services component. During the recession of 2007–2009, sentiment is found to have a more pervasive effect on all components of aggregate consumption: durables, non-durables and services. Copyright © 2015 John Wiley & Sons, Ltd.

We analyze forecasts of consumption, nonresidential investment, residential investment, government spending, exports, imports, inventories, gross domestic product, inflation, and unemployment prepared by the staff of the Board of Governors of the Federal Reserve System for meetings of the Federal Open Market Committee from 1997 to 2008, called the Greenbooks. We compare the root mean squared error, mean absolute error, and the proportion of directional errors of Greenbook forecasts of these macroeconomic indicators to the errors from three forecasting benchmarks: a random walk, a first-order autoregressive model, and a Bayesian model averaged forecast from a suite of univariate time-series models commonly taught to first-year economics graduate students. We estimate our forecasting benchmarks both on end-of-sample vintage and real-time vintage data. We find that Greenbook forecasts significantly outperform our benchmark forecasts for horizons less than one quarter ahead. However, by the one-year forecast horizon, typically at least one of our forecasting benchmarks performs as well as Greenbook forecasts. Greenbook forecasts of the personal consumption expenditures and unemployment tend to do relatively well, while Greenbook forecasts of inventory investment, government expenditures, and inflation tend to do poorly.

In this study a comparative analysis of the forecasts accuracy for Spain (developed country) and Romania (developing country) was developed for the crisis period (2009 - 2013). The providers are national forecasters: Bank of Spain and FUNCAS (Spanish Savings Banks Foundation) for Spain and two anonymous experts for Romania (E1 and E2). Only for the unemployment rate the Spanish institutes provided more accurate forecasts, for the rest of the variables (inflation rate, private consumption and GDP growth) the Romanian institutes giving more accurate predictions. However, the results are contradictory for the accuracy assessment in each country, the U1 Theil's statistic and the accuracy tests (Diebold-Mariano test and Wilcoxon's signed rank test) indicating different hierarchies. All in all, for inflation rate, unemployment rate and GDP growth in Romania, E2 provided more accurate forecasts. In Spain, FUNCAS offered better forecasts for GDP growth and private consumption during 2009 - 2013.

The Great Recession of 2007:IV-2009:II sparked great interest in understanding uncertainty and its effects on the macroeconomy. This paper introduces a new approach to measure uncertainty. We start from the same premise as in Jurado et al. (2014), that is: "What matters for economic decision making is whether the economy has become more or less predictable; that is, less or more uncertain." However, as opposed to Jurado et al. (2014), the uncertainty index we propose relies on the unconditional likelihood of the observed outcome. More specifically, our proposed index is the percentile in the historical distribution of forecast errors associated with the realized forecast error.

Standard economic models assume that the demand for expert predictions arises only under the conditions in which individuals are uncertain about the underlying process generating the data and there is a strong belief that past performances predict future performances. We set up the strongest possible test of these assumptions. In contrast to the theoretical suggestions made in the literature, people are willing to pay for predictions of truly random outcomes after witnessing only a short streak of accurate predictions live in the lab. We discuss potential explanations and implications of such irrational learning in the contexts of economics and finance. © 2015 The President and Fellows of Harvard College and the Massachusetts Institute of Technology

We apply meta regression analysis to a unique data set of 104 studies on multiplier effects with 1069 reported multipliers in order to derive stylized facts and to quantify the differing effectiveness of the composition of fiscal impulses, adjusted for the interference of study-design characteristics and sample specifics. As a major result, we find that public spending multipliers are close to one and about 0.3 to 0.4 units larger than tax and transfer multipliers. Public investment multipliers are even larger by approximately 0.5 units. Reported multipliers vary with study-design, thus, policy consulting based on a certain multiplier study should lay open by how much specification affects the results. Our meta analysis provides guidance concerning influential factors, their sign and magnitude.

This paper exploits a data rich environment to provide direct econometric estimates of time-varying macroeconomic uncertainty, defined as the common volatility in the unforecastable component of a large number of economic indicators. Our estimates display significant independent variations from popular uncertainty proxies, suggesting that much of the variation in the proxies is not driven by uncertainty. Quantitatively important uncertainty episodes appear far more infrequently than indicated by popular uncertainty proxies, but when they do occur, they are larger, more persistent, and are more correlated with real activity. Our estimates provide a benchmark to evaluate theories for which uncertainty shocks play a role in business cycles.

We study forecasts of real GDP growth using a large panel of individual forecasts from 36 advanced and emerging economies over the period 1989–2010. We show that the degree of information rigidity in average forecasts is substantially higher than that in individual forecasts. Individual-level forecasts are updated quite frequently, a behavior which is more in line “noisy” information models (Woodford, 2002; Sims, 2003) than with the assumptions of the sticky information model (Mankiw & Reis, 2002). While there are cross-country variations in information rigidity, there are no systematic differences between advanced and emerging economies.

Die amtliche Statistik hat die Angaben zum Bruttoinlandsprodukt der ostdeutschen Flächenländer für die Jahre seit 2000 um jährlich rund 3% erhöht. In dieser Korrektur kommen auch konzeptionelle Erweiterungen des gesamtwirtschaftlichen Rechnungswesens zum Tragen. Insbesondere betrifft das Forschungs- und Entwicklungsleistungen, die jetzt wie eine Investition in ein Vermögensgut behandelt werden. Es zeigt sich, dass der Osten in diesem Zukunftsbereich gegenüber dem Westen stärker zurückliegt, als bisher beziffert worden ist.

This study is intended to demonstrate that the downturn in fixed capital formation and investment surpassed the decline in GDP; among the OECD countries Hungary witnessed the 9th largest shortfall of the investment rate compared to pre-crisis levels. The growth rate of Hungarian working capital outflows surpassed that of FDI inflows. The service fee payment of PPP investment contributed to the budget deficit by around 0.5 per cent of GDP per annum. The structure of whole-economy fixed investment underwent a considerable transformation: manufacturing saw a spectacular expansion, while the share of public administration and water supply grew to a lesser degree. The contribution of real estate, electricity and gas supply, education and transportation decreased markedly. The structural changes in public sector investment are reflected in the output of fixed capital formation, which increased by 2.1 in the central budget and by 12.3 per cent at local governments. The total amount of investment grants doubled in the period between 2009 and 2013. In the sector of non-financial corporations, the ratio of grants to GDP rose to 1.3 per cent in 2011, 1.4 per cent in 2012, and 1.9 per cent in 2013 compared to 1.2 and 1.1 per cent in 2009 and 2010, respectively. Besides net EU transfers, the expansion of grants was also an important contributor to the upswing in investment activity in 2013–2014.

Az európai növekedési potenciál fokozatos, ám több évtizeden át látens eróziója az elmúlt másfél évtizedben - versenyképességi és alkalmazkodási problémáinak kiéleződésével párhuzamosan - egyre nyíltabb formában jelent meg. Az EU-15 országai termelékenységének felzárkózása az Egyesült Államokéhoz - fokozatos mérséklődés után - az 1990-es évek közepén megtört, majd növekedési dinamikája egyre inkább elmaradt fő versenytársáétól. A teljes tényezőtermelékenységbeli különbségek csekély számú iparágban összpontosulnak: az elektronikai berendezések előállítása, a nagy- és a kiskereskedelem, az ingatlan- és egyéb üzleti szolgáltatások, illetve a pénzügyi szolgáltatások területén. A fő okok a termék- és munkaerőpiacok működésének eltéréseiben, az Egyesült Államokat jellemző intenzívebb versenykörülményekben, illetve egyes európai részpiacok túlszabályozásában keresendők. Lényeges szerepet játszanak továbbá az innovatív szektorok adminisztratív és pénzügyi belépési korlátai. Journal of Economic Literature (JEL) kód: E27, F15, F43, O40, O47., Gradual, latent erosion of European growth potential over several decades - parallel exacerbation of problems of competitiveness and adaptation - has been appearing in an increasingly open form. The improvement in the productivity of the EU 15 countries compared with the United States eased steadily and then ceased in the mid-1990s, after which its growth dynamic fell behind that of its main competitor. The whole factor-productivity differences were centred on a small number of industries: production of electronic equipment, wholesale and retail trading, real-estate and other commercial services, and financial services. The main causes can be sought in differences in the operation of product and labour markets, the more intensive competition conditions characteristic of the United States, and the excessive regulation of certain partial European markets. An essential role is also played by the administrative and financial entry restrictions on innovative sectors.

This paper develops a dynamic structural life-cycle model to study how heterogeneous health and medical spending shocks a¤ect the savings behavior of the elderly. Individuals are allowed to respond to health shocks in two ways: they can directly pay for their health care expenses (self-insure) or they can rely on health insurance contracts. There are two possible insurance options, one through formal contracts and another through informal care provided by family. Formal contracts may be a¤ected by asymmetric information problems, whereas informal insurance depends on social ties (cohesion) and on bequeathable wealth. I estimate the model on SHARE data using simulated method of moments for four levels of wealth in a sample of single retired Europeans. Counterfactual experiments show that health, medical spending and health insurance are indeed the main drivers of the slow wealth decumulation in old age. I also fi?nd that social cohesion rises with age, declines with wealth and is higher in Mediterranean countries than in Central European and Scandinavian countries. Finally, high social cohesion appears typically associated with increased life expectancy.

When forecasting, all available information should be used. As the most recent indicators are mostly published in monthly or higher frequency while the GDP is released in quarterly frequency, this can pose a problem in an econometric framework. This paper presents the KOF short-term indicator for international forecasts, which uses both bridge equations as well as a MIDAS approach. The forecast performance of the models is then assessed by conducting a real-time experiment using a reduced dataset for the US. Even with this reduced set forecast performance can be increased by up to 25 percent in comparison to an autoregressive model.

The Vision of the Eco-Bio-Economy is to sustain development of the humankind welfare in all forms, through an economy of future dedicated to human life through the rational use of the environmental resources. The present work attempts to discuss the issues that humanity faces at the beginning of a new global economic paradigm. The minimum point of the financial crisis started in 2008 meets the final years of the decline phase of the long term global economic cycle. The feeling is one of lack of vision on the part of Governments, of improvisation, of passive reaction, such as seeing and doing. One feels that the economic context is worn out , dysfunctional because of deep recovery problems. The perception, not far from the taugh reality, is that of a national competition meant to minimize losses caused by the financial crisis and to use beggar thy neighbor types of policies, similar to finding the way out of the crisis on the expense of others.

In the recent literature on nowcasting, the use of the so-called bridge models is advocated. These are simple regression models that use data on mixed frequencies, usually with the lower frequency data serving as dependent variables and the higher frequency data as explanatory variables. In this note we investigate whether the use of such models can lead to performance enhancements in forecasting real GDP growth for Greece. This is an interesting and instructive exercise because of the obvious break in Greek real GDP growth during the crisis but also, and more importantly, because of the potential usefulness of such models in forecasting the anticipated recovery in Greek growth. Since many monthly activity indicators are released in advance of GDP growth it is interesting to see how the structure and timing of bridge models can lead to potential improvements in forecasting growth. Our results indicate that by using three of the most important monthly activity indicators such performance enhancements are indeed possible.

This paper investigates the properties of distortions that manifest themselves as wedges in the equilibrium conditions of the neoclassical growth model across a sample of 22 OECD countries for the 1970–2011 period. The quantitative relevance of each wedge and its robustness in generating fluctuations in macroeconomic aggregates is assessed. The efficiency wedge proves to be determinant in enabling models to replicate movements in output and investment, while the labor wedge is important to predict fluctuations in hours worked. Modeling distortions to the savings decision holds little quantitative or qualitative relevance. Also, investment seems to be the hardest aggregate to replicate, as prediction errors concerning output and hours worked are typically one order of magnitude smaller. These conclusions are statistically significant across the countries in the sample and are not limited to output drops. Finally, the geographical distance between countries and their degree of openness to trade are shown to contain information with regard to the wedges, stressing the importance of international mechanisms of transmission between distortions to the equilibrium conditions of the neoclassical growth model.

This study engineers a household sector where individuals process macroeconomic information to reproduce consumption spending patterns in New Zealand. To do this, heterogeneous artificial neural networks (ANNs) are trained to forecast changes in per worker consumption. In contrast to existing literature, results suggest that there exists a trained ANN that significantly outperforms a linear econometric model at out-of-sample forecasting. To improve the accuracy of ANNs using only in-sample information, methods for combining private knowledge into social knowledge are explored. For one type of ANN, relying on an expert is beneficial. For most ANN structures, weighting an individual"s forecast according to how frequently that individual"s ANN is a top performer during in-sample training produces more accurate social forecasts. By focusing only on recent periods, considering the severity of an individual"s errors in weighting their forecast is also beneficial. Possible avenues for incorporating ANN structures into artificial social simulation models of consumption are discussed.

Only strong economic growth will help Europe emerge from its crisis. The reforms implemented to date at national and European level have failed to impact the economypositively; this is due to excessive national, corporate, and private debts, the flawed banking system, the lack of structural reforms, an insufficient institutional framework at European level, as well as a persisting climate of distrust in the stability of economic development. The probability of economic stagnation, which is marked by high unemployment, declining incomes, decelerating potential growth, and deflation, is high and has increased significantly. The risk of economic development in Europe following Japan's example of the 1990s is very real indeed. This Economic Bulletin shows that one of Europe's biggest economic weaknesses is a lack of private investment and that a European investment agenda is vital in order to generate the impetus required to push the European economy towards a sustainable recovery. European economic policy should focus not on higher public spending, but on increasing private investment as well as creating markets that function properly.

The present paper is centred on the analysis of a basic, classical, closed economy dynamic stochastic general equilibrium model, revealing some core economic variables, captured at the level of our country, both from the perspective of their reaction to the shock on technology and from the one relating to their evolution on medium to long term. After a brief rendering of the problems maximised and solved, given the constraints, by the two economic agents considered, households and firms, as well as subsequent to the presentation of the equilibrium established on the market of goods and services, the final equations are selected and implemented in Dynare, a specific tool of Matlab. The numeric results obtained and the related graphical representations are thereafter construed, the end purpose being the formulation of several suggestions regarding the appropriate economic decisions to be made in the future, by the entitled entities, in order to lay the grounds of a desirable economic growth.

In this article we seek to estimate the Brazilian “Okun’s law” with quarterly data ranging from 1980Q1 until 2013Q3. Considering the typical Okun's relationship, Δu=α - βΔy, where “β” is the Okun coefficient, we have obtained estimates of β between -0.1878 and -0.2055, such values are similar to those of Italy (-0.21) and greater than the value of Japan (-0.12), but lower than those in countries like the UK (-0.58), USA (-0.52), France (- 0.43) and Germany (-0.38); the latter values were estimated by Sogner and Stiassny (2002).

Since reducing the possibility of risks that can be avoided – including risks associated with the uncertainty of the future – is of great importance in the economic arena, generations of economists have struggled and are still struggling (with mixed results) to develop ‘reliable’ forecasting techniques. Although some Hungarian organisations publish macroeconomic forecasts on a regular basis, their margins of error are rarely taken into account. For this reason, the authors examine how well actual processes are foreseen by the numerical forecasts published by the GKI Economic Research Co. for the next year. Their analyses are based on a 17-year comparable database, and present the development over time of indicators prognosticated and then published in statistics, take account of their differences (so-called estimation errors) and standard deviations, as well as the correlations of forecasts and statistics. They find that (in Hungary at least) the trends of certain indicators, the development of inflation or the GDP for instance, can in most cases be forecasted quite accurately, while other macroeconomic indicators (financial equilibrium indexes for example) and the turning points of business cycles in general can only be foreseen with considerable margins of error. Based on the above, they consider it necessary that economic policy take the margins of error of macroeconomic forecasts into consideration at all times.

The GDP forecasting is a prior concern for each country, but also for an entire region composed by more countries with specific and different evolutions of GDP. The GDP predictions for the 27 European Union are based on two econometric techniques. It was proved, using accuracy indicators like U1 and U2 Theil’s coefficients and statistical tests (Morgan-Granger-Newbold test, Harvey-Leybourne-Newbold test and Diebold-Mariano test) that the aggregation of forecasts made for each country in the EU on horizon 2011-2013 provided better forecasts than the use of a single semi-logarithmic model for the entire region. However, the naïve forecasts gave more accurate results than the proposed models, this conclusion being in accordance with the recent results in literature regarding GDP forecasting. For 2013 the ex-ante evaluation of forecasts was made, considering that the actual value is the one registered in 2012. It is anticipated an underestimation of the GDP rate according to the aggregation technique if the benchmark is the indicator’s value in 2012.

Official monthly unemployment data is unavailable in China, while intense public interest in unemployment requires timely and accurate information. Using data on web queries from lead search engines in China, Baidu and Google, I build two indices measuring intensity of online unemployment-related searches. The unemployment-related search indices identify a structural break in the time series between October and November 2008, which corresponds to a turning point indicated by some macroeconomic indicators. The unemployment- related search indices are proven to have significant correlation with Purchasing Managers¡¯ Employment Indices and a set of macroeconomic indicators that are closely related to changes in unemployment in China. The results of Granger causality analysis show that the unemployment-related search indices can improve predictions of the macroeconomic indicators. It suggests that unemploy- ment-related searches can potentially provide valuable, timely, and low-cost information for macroeconomic monitoring.

This article highlights the results of the second part of a study exploring the possibility of implementing the IFRS international standards in Romania and the potential effects that may occur due to the adoption of this standard. In the second part of the study we aim to determine the difficulties encountered by the companies in adopting the IFRS provisions and the obstacles regarding the implementation of IFRS in Romania. Also, we asked for the opinion of the respondents regarding the current Romanian laws and we asked them to suggest a solution so that the discrepancies between the Romanian laws and the IFRS to be diminished or eliminated.

A main problem for macroeconomic studies continues to be the estimation of capital stock and some derived indicators like coefficient of capital, depreciation rate, etc. In this way we are proposing a simple and intuitively model in order to estimate such basic macroeconomic indicators but avoiding to knowing the amount of capital stock. By applying a simulation model in case of European Union data for a set of periods, we obtained some relevant result. One of them is referring to the negative impact of last global crisis on the coherence of a classic type model. Such model is adequate mostly for a period of continuous increasing in GDP as it was for EU during the period 2000-2007.

This article proposes an empirical econometric approach to improve the degree of accuracy for predictions made by Romanian experts in forecasting. Several fixed-effects models are constructed using the inflation and unemployment rate actual values and the forecasts provided by the European Commission, the National Commission for Prognosis and Dobrescu’s model over 2001-2014. The predictions based on these fixed-effects models did not improve the forecasters’ accuracy, but combined predictions of these models and naive forecasts brought a statistically significant improvement for projections made by Romanian forecasters on the horizon 2011-2013. This assumption was proved by common accuracy measures and Diebold-Mariano test.

This article examines the FDI in Romania using the autoregressive distributed lag model (ARDL) compared with conventional (error correction model) ECM. The results based on the bounds testing procedure implemented by Pesaran in 2001, confirm that a stable, long-run relationship exists between FDI and GDP, trade and labour in Romania. Our results also reveal that after applying the ARDL model we obtain the same results of long run association as in applying the conventional ECM models.

Im Zuge der Wirtschafts- und Finanzkrise ist die ohnehin nicht kräftige Investitionstätigkeit in Europa und insbesondere im Euroraum eingebrochen; in Relation zum Bruttoinlandsprodukt sind die Bruttoanlageinvestitionen seit 2008 um vier Prozentpunkte gesunken. Schon vor der Krise war in Teilen des Euroraums - darunter in Deutschland - die Investitionstätigkeit gemessen an den gesamtwirtschaftlichen Bedingungen eher schwach; darauf weisen Modellsimulationen hin. Insbesondere in den südeuropäischen Volkswirtschaften hingegen waren die Investitionen - vor allem im Wohnungsbau - in der Vorkrisenzeit ausgesprochen hoch, waren aber zu wesentlichen Teilen durch Kapitalzuflüsse aus dem Ausland finanziert. Im Zuge der Krise sind die ausländischen Direktinvestitionen und mit ihnen die Investitionstätigkeit eingebrochen, ohne dass dies bisher durch höhere Investitionen in anderen Teilen der Währungsunion ausgeglichen würde. Im Ergebnis liegen amaktuellen Rand die Investitionen im Euroraum deutlich unter dem Niveau, das den gesamtwirtschaftlichen Bedingungen entspräche; im Zeitraum zwischen 2010 und2012 wurden daran gemessen im Durchschnitt etwa zwei Prozent in Relation zum Bruttoinlandsprodukt zu wenig investiert. Damit verbunden sind erhebliche Wachstumseinbußen in der kurzen wie in der langen Frist, da der für die Expansion der Produktionsmöglichkeiten erforderliche Kapitalstock nur langsam wächst: Wäre die Investitionstätigkeit im Euroraum entsprechend höher gewesen, so hätte das Potentialwachstum in der Währungsunion seit der Krise um jahresdurchschnittlich 0,2 Prozentpunkte höher liegen können als tatsächlich beobachtet. In the course of the economic and financial crisis, investment activity, which was not very strong to begin with, in Europe and especially the Eurozone caved in. In relation to gross domestic product, fixed capital formation declined by four percentage points since 2008. Already prior to the crisis, investment activity was rather weak in parts of the Eurozone - amongst others in Germany. This finding is indicated by model simulations which account for country-specific macroeconomic conditions. On the other hand, especially in southern European economies, investment - mostly in the home construction sector - was markedly high before the crisis. These investments were however mainly financed by capital inflows from abroad. In the course of the crisis, foreign direct investment slumped and so did investment activity in these countries which has not been counterbalanced by higher investments in other parts of the monetary union. As a result, current investment in the Eurozone remains markedly below the level corresponding to macroeconomic conditions. When measured against this baseline, there was an underinvestment of around two percent on average in relation to gross domestic product between 2010 and 2012. This is associated with significant reductions in growth in the short and long run since the capital stock needed to maintain production capacity is growing rather slowly. If investment activity in the Eurozone had been correspondingly stronger, potential growth in the monetary union could have been 0.2 percentage points higher than observed since the crisis.

The theme of the present research refers to the possibility of implementing the international IFRS standards in Romania as well as to the eventual effects which may occur as a result of the adoption of this decision, taking into account that the leveling of the international accounting standards currently in force, becomes more and more necessary and this is the reason why we proceeded to the elaboration of an “Empirical study about the impact of the IFRS implementation in Romania”. Considering that an enhanced convergence of the national regulation with the international ones is required, such a study is necessary to identify the difficulties, costs but also the eventual suggestions necessary to make the implementation process as much as possible accessible to those involved with. We selected this theme because the subject is up-to-date and has a particular importance. In this first part of the study presented by this paper we aim to determine the general profile of the respondents regarding age, experience in the accounting field and IFRS, the general profile of the company they represent, as well as the activities performed prior to using the IFRS and the costs incurred by reporting as per IFRS provisions.

In this paper we propose a modification of the Dynamic Theil's Entropy that considers the inequality in the whole population. We decompose it into three addends and we show how to compute them within a Markov model of income evolution. In this way the income inequality can be measured in the whole population and not only among a given number of classes in which the economic agents are classified. The model is implemented with statistics from Eurostat data applied on France, Germany, Greece and Italy. The results reveal different inequality behaviors characterizing the considered European countries.

In the course of the economic and financial crisis, investment activity, which was not very strong to begin with, in Europe and especially the Eurozone caved in. In relation to gross domestic product, fixed capital formation declined by four percentage points since 2008. Already prior to the crisis, investment activity was rather weak in parts of the Eurozone — amongst others in Germany. This finding is indicated by model simulations which account for country-specific macroeconomic conditions. On the other hand, especially in southern European economies, investment — mostly in the home construction sector — was markedly high before the crisis. These investments were however mainly financed by capital inflows from abroad. In the course of the crisis, foreign direct investment slumped and so did investment activity in these countries which has not been counterbalanced by higher investments in other parts of the monetary union. As a result, current investment in the Eurozone remains markedly below the level corresponding to macroeconomic conditions. When measured against this baseline, there was an underinvestment of around two percent on average in relation to gross domestic product between 2010 and 2012. This is associated with significant reductions in growth in the short and long run since the capital stock needed to maintain production capacity is growing rather slowly. If investment activity in the Eurozone had been correspondingly stronger, potential growth in the monetary union could have been 0.2 percentage points higher than observed since the crisis.