The long-run determinants of inequality: What can we learn from top income data?

This paper studies determinants of income inequality using a newly assembled panel of 16 countries over the entire twentieth century. We focus on three groups of income earners: the rich (P99–100), the upper middle class (P90–99), and the rest of the population (P0–90). The results show that periods of high economic growth disproportionately increases the top percentile income share at the expense of the rest of the top decile. Financial development is also pro-rich and the outbreak of banking crises is associated with reduced income shares of the rich. Trade openness has no clear distributional impact (if anything openness reduces top shares). Government spending, however, is negative for the upper middle class and positive for the nine lowest deciles but does not seem to affect the rich. Finally, tax progressivity reduces top income shares and when accounting for real dynamic effects the impact can be important over time.     

What can we learn from the distribution of trade patterns?

This paper proposes an empirical framework for analyzing the dynamics of trade specialization, using a symmetric transformation of the standard Balassa (Manch Sch Econ Soc Stud 33(2):99–123, 1965) index and the conditional density estimation methods suggested by Hyndman et al. (J Comput Graph Stat 5(4):315–336, 1996). The framework is implemented using data on the cross-sector export and import specialization of the four initial EU Cohesion countries over the last 40 years. We discuss the importance of studying both the distribution’s external shape and the intra-distribution dynamics and why it is interesting to include imports in the analysis. We find a reduction of the overall degree of export specialization in Portugal, Greece and Spain. Conversely, Ireland has the strongest export specialization and there is evidence of an increase over time. The export intra-distribution dynamics reveal persistence of the specialization status in the four countries, especially for high values of the index. In all countries, the degree of specialization is higher for exports than for imports and intra-distribution dynamics reveal more mobility of import specialization than that of exports.     

What can we learn from revisions to the Greenbook forecasts?

Although there have been many evaluations of the Federal Reserve’s Greenbook forecasts, we analyze them in a different dimension. We examine the revisions of these forecasts in the context of fixed event predictions to determine how new information is incorporated in the forecasting process. This analysis permits us to determine if there was an inefficient use of information in the sense that the forecast revision has predictive power for the forecast error. Research on forecast smoothing suggests that we might find a positive relationship between the forecast error and the forecast revision. Although we do find for some variables and horizons the Fed’s forecast errors are predictable from its forecast revisions, there is no evidence of forecast smoothing. Instead the revisions sometimes have a negative relationship with the forecast error, suggesting in these cases that the Fed may be over-responsive to new information.     

What can we learn from a large border effect in developing countries?

Failure of the law of one price (LOP) in the short run is an empirical regularity. Recent research, using disaggregated price data for different cities across an international boundary, has shown that the variation of the prices in equidistant cities located in two different countries is systematically larger than that for the cities within the same country. Nontariff barriers and exchange rate variability are cited as the proximate causes of this systematic difference in consumer price variability. Results using data from developing countries with large nontariff barriers and more volatile exchange rate suggest that those claims are overemphasized.     

On the economic factors of deforestation: What can we learn from quantile analysis?

The deforestation factors at a global level have been widely studied in the empirical economic literature. However, the high heterogeneity among countries considerably limits the overall significance of the results. Using quantile approach, we show thatsome major deforestation factors are more prevalent in high deforestation countries, giving the insight that those factors have been under-estimated in previous studies.     

Peaks or tails – What distinguishes financial data?

We argue against the view that it is mostly the peaks of the empirical densities of stock returns (and of other risky returns as well) that set such data aside from “normal” variables. We show that peaks depend on sample size and on the way returns are standardized, and that for given data sets of stock returns, both higher peaks and lower peaks than in a standard normal case can be obtained. First version received: March 1998/Final version received: April 2000     

Functional food consumption and depression among the elderly — What can we learn from a longitudinal survey?

Depressive syndromes among the elderly have been recognized as important public health issues. This study contributes to this issue by investigating the causal effect of functional food consumption on depression among the elderly using a unique panel dataset of 1480 individuals drawn from a national representative survey of Taiwanese elderly in 1999, 2003 and 2007. In addition to estimating a standard individual fixed effect model, a random trend fixed effect model which allows for both unobserved individual-specific time invariant and variant factors is estimated. The results of the random trend model point to a significant and negative effect of functional food consumption on depression among the elderly. However, an insignificant effect is predicted by the standard fixed effect model. In addition to functional food consumption, living arrangement with children and engagement in the social activities of the elderly also significantly decrease the likelihood of the elderly becoming depressed.     

What can we learn from the history of gasoline crack spreads?: Long memory,structural breaks and modeling implications

In this paper, we investigate the long-range auto-correlations of crack spreads using a nonparametric method, named detrended moving average (MF-DMA). We find that the auto-correlations display multiscaling behaviors and are dominated by the anti-persistence (mean-reversion) in the long-term. Moreover, the auto-correlations are multifractal, indicating that various small and large fluctuations display different scaling behaviors. Using a technique of rolling windows, we find that some extreme events can drive the degree of anti-persistence and the multifractality (complexity) to rise up. In other words, these events have negative impacts on market efficiency. However, the effects of these events are not alike. We also detect long-range auto-correlations in crack spread volatilities and find a strong persistent behavior and multifractality. Finally, we discuss the modeling implications of the findings on long-range auto-correlated patterns. Our results indicate that ARFIMA-GARCH models can capture the major dynamics of large fluctuations. For small fluctuations, they are misspecified. Interestingly, we find that the strong long-range auto-correlated behaviors do not imply that ARFIMA model which takes long memory into account can outperform random walk model in the sense of out-of-sample prediction. The major reason may be that market complexity exploited in this paper causes the low predictability of ARFIMA model.     

What can eastern European countries learn from the Slovak economy? A twin deficit growth approach

This paper applies an extended growth model to the Slovak economy and explains the potential pitfalls that a transition economy faces on the way to converging with other advanced European countries. Our empirical analysis shows that Slovakia grew at a higher rate than that allowed by the balance-of-payments equilibrium rate and that this is consistent with the accumulation of trade deficits over time. A scenarios analysis shows that improving trade competitiveness, changing import and export shares toward a current account balance, and financing the economy at a lower cost will be the most successful ways to achieve higher growth.     

The presence of unemployment hysteresis in the OECD: what can we learn from out-of-sample forecasts?

This paper investigates the relevance of unemployment hysteresis in seventeen OECD countries. We employ an out-of-sample forecast exercise in which a mean-reverting autoregressive model is compared to an autoregressive model with an imposed unit root. A substantial difference in forecasting performance between the two models is established for many countries, but the results are mixed in their strength. The evidence for unemployment hysteresis in Austria, Finland, Iceland, Israel, Italy, Japan and Sweden is, however, convincing. For no country can unambiguous support for a mean reverting unemployment rate be found.     

Wealth Inequality in Sweden: What can we Learn from Capitalized Income Tax Data?

This paper presents new estimates of wealth inequality in Sweden during 2000–2012, linking wealth register data up to 2007 and individually capitalized wealth based on income and property tax registers for the period thereafter when a repeal of the wealth tax stopped the collection of individual wealth statistics. We find that wealth inequality increased after 2007 and that more unequal bank holdings and housing appear to be important drivers. We also evaluate the performance of the capitalization method by contrasting its estimates and their dispersion with observed stocks in register data up to 2007. The goodness‐of‐fit varies tremendously across assets and we conclude that although capitalized wealth estimates may well approximate overall inequality levels and trends, they are highly sensitive to assumptions and the quality of the underlying data sources.     

Big data analytics in economics: What have we learned so far,and where should we go from here?

Research into predictive accuracy testing remains at the forefront of the forecasting field. One reason for this is that rankings of predictive accuracy across alternative models, which under misspecification are loss function dependent, are universally utilized to assess the usefulness of econometric models. A second reason, which corresponds to the objective of this paper, is that researchers are currently focusing considerable attention on so‐called big data and on new (and old) tools that are available for the analysis of this data. One of the objectives in this field is the assessment of whether big data leads to improvement in forecast accuracy. In this survey paper, we discuss some of the latest (and most interesting) methods currently available for analyzing and utilizing big data when the objective is improved prediction. Our discussion includes a summary of various so‐called dimension reduction, shrinkage and machine learning methods as well as a summary of recent tools that are useful for ranking prediction models associated with the implementation of these methods. We also provide a brief empirical illustration of big data in action, in which we show that big data are indeed useful when predicting the term structure of interest rates.     

What are we learning from the life satisfaction literature?

The recent availability of cross-sectional and longitudinal survey data on life satisfaction in a large number of countries gives us the opportunity to verify empirically (and not just to assume) what matters for individuals and what economists and policymakers should take into account when trying to promote personal and societal well-being. We now have ample evidence, generally robust to different cultural backgrounds, on the effects of some important happiness drivers (income, health, unemployment, marital status, etc.) which can be considered “quasi-stylized facts” of happiness. If economic policies, for many obvious reasons, cannot maximize self-declared life satisfaction as such, we are nonetheless learning a lot from these findings. In particular, results on the relevance of relational goods, on the inflation/unemployment trade-off in terms of welfare and, more in general, on the measurement of the shadow value of non-market goods obtained with life satisfaction estimates are conveying relevant information about individual preferences and what is behind utility functions. Such findings suggest that the anthropological reductionism characterizing most economic models can be misleading and that target indicators of economic policies have to be refocused if we want to minimize the distance between economic development and human progress.     

Fiscal sustainability and demographics – Should we save or work more?

Approaching demographic shifts are raising concerns about fiscal sustainability in most OECD countries. A widespread view based on the tax-smoothing idea is that a prior consolidation of public finances is required to cope with the predicted trend deterioration in the primary budget balance. However, the smoothing argument cannot unconditionally be applied to the demographic problem. It is important to distinguish between increases in the dependency ratio driven by changes in fertility and longevity. For the former the smoothing argument may be appropriate, but not for the latter. In the case of longevity, a trade-off between consolidation and increasing retirement ages becomes relevant, and there are strong arguments why the latter should be pursued by e.g. linking statutory retirement ages to longevity. Both positive aspects in assessing the order of magnitude of sustainability problems and normative aspects of formulating policy strategies are addressed.     

R&D Spillovers through Student Flows,Institutions, and Economic Growth: What can we Learn from African Countries?

Using modern panel cointegration estimation techniques, this paper examines whether tertiary student flows can effectively transmit technological knowledge from industrialized countries to African countries. The results obtained lend strong support to this hypothesis. In addition, this paper extends the analysis to include institutional variables such as the ease of doing business, legal origins, and religious majority to see if institutional characteristics have any impact on the way knowledge diffusion affecting total factor productivity (TFP). However, it is not clear that institutional differences are important factors that influence the degree of R&D spillovers and, hence, the TFP of African countries.     

How can a strong currency or drop in oil prices raise inflation and the black-market premium?

Based on the case of Venezuela, an oil exporter with a multiple exchange rate regime, this paper explains two counterintuitive phenomena. First, a fall in oil revenue can drive a steep rise in inflation by reducing foreign exchange for imports and raising the fiscal deficit financed by money growth. Second, when foreign exchange is rationed, a devaluation of the official exchange rate could produce a transitory fall in inflation by reducing the fiscal deficit and subsidies for buying foreign exchange. The paper also shows that the black market exchange rate can be rising far faster than overall inflation if it is driven by prices in the most distorted goods markets. The channels emphasized in this paper for determining inflation and the black market exchange rate are novel in the literature and may provide avenues of future research on commodity exporters and foreign exchange constraints.     

What explains consumption in the very short-run? Evidence from checking account data

This paper investigates consumption behavior within an intertemporal optimization model of the representative household. Our dataset consists of deposits and withdrawals from individual household checking accounts that received paychecks by direct deposit. We construct samples of panel data for households with weekly, biweekly, and semi-monthly pay-periods and form two different measures of consumption for each sample. GMM estimates of structural parameters provide mixed evidence for habit formation or durability and limited support for the permanent income hypothesis. The results instead point to “rule of thumb” consumption under liquidity constraints, where the household consumes its current disposable income each pay-period with possible debt servicing. These findings are uniform with regard to estimation of sub-samples split according to age or household income.     

Long-run waves or short-run fluctuations – what establishes the correlation between oil and food prices?

The strong correlation between food prices and energy prices has gained much attention in the public debate. In this article, we focus on the so-called excess co-movement, which is the correlation between crude oil price and the prices of food commodities after controlling for economic activity. We use a frequency domain Granger causality test to analyse short-run and long-run relationships between crude oil prices and prices of food commodities. For important biofuel inputs like maize, soybeans, rapeseed and EU sugar, we find evidence for long-run Granger causality in particular for the period after 2007. This supports the hypothesis that the increasing biofuel production creates the link between the prices of crude oil and food commodities. However, we also find short-run Granger causality for various food commodities. This result is more in line with herd behaviour or speculation in commodity markets.     

Do oil price changes really matter to the trade balance? Evidence from Korea-ASEAN commodity trade data

The contribution of this article is to assess the effect of oil prices have on the trade balance in the framework of bilateral commodity trade data between Korea and each of the four ASEAN member countries—Indonesia, Malaysia, Singapore, and Thailand. To examine this subject thoroughly, we first assume the effects of oil price changes to be symmetric and apply the linear autoregressive distributed lag (ARDL) method to the subject. We find that the price of crude oil indeed has an important role in affecting Korea's trade balance with those four ASEAN economies in both the long- and short-run. We then separate oil price hikes from oil price plunges and implement the nonlinear ARDL method to reveal that there is evidence that changes in oil prices appear to have asymmetric effects on the trade balance for certain products in the long- and short-run.