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.     

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.     

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.     

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.     

R&D activities in start-up firms: What can we learn from founding resources?

Research and development is critical in promoting innovation and firm development. While many studies have been discussing how firms’ R&D behaviour is affected by the internal factors and external factors, little has been done to link it to firms’ founding conditions. Using resource-based view theory, this study suggests the firms’ R&D activities in their later stages are partly determined by firms’ starting resource bundle. We propose that the financing structure, entrepreneurs’ education background and intellectual property of the new firms will affect their R&D behaviour. The study examines the performance of a random sample of firms established in 2004 using data from the Kauffman Firm Survey. The result shows a mixing impact of firms’ starting resources. The founders’ education and the ownership of intellectual property have a positive and long-lasting impact, while firms’ financial capital matters mostly in the short term. The study also finds subsequent resource development is highly reliant on the initial resource bundle.     

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.     

Sticky prices or rational inattention – What can we learn from sectoral price data?

This paper derives stylised facts on sectoral inflation dynamics and confronts these facts with two popular theoretical models of price setting. Based on sectoral price responses to macroeconomic shocks estimated from an approximate factor model, we find that the frequency of price changes explains a relevant share of the cross-sectional variation of the speed and size of responses. Moreover, there is little evidence that the volatility of sectoral inflation due to idiosyncratic shocks dampens the size and speed of the responses to macroeconomic shocks. These findings support a multi-sector model with sticky prices rather than a rational-inattention model. We derive the results from different modelling and sampling decisions proposed in the literature, and we find that the explanatory power of the frequency of price changes for the speed of response to a macroeconomic shock proves robust in the face of these decisions. Other results are sensitive with respect to the choice of the factor model and the treatment of outliers.     

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 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.     

Ukraine's unconsidered losses from the annexation of Crimea: What should we account for in the DCFTA forecasts?

In March 2014 Crimea unilaterally declared its independence from Ukraine and joined the Russian Federation. The separation of a part of a state's territory and economy is an interesting matter to examine. The economy of Ukraine has not only shrunk, but also changed its structure as Crimea had a quite distinct production pattern compared to the rest of Ukraine. Moreover, policy measures initialized before the separation may have different effects once applied only to a part of the former economy. This paper proposes a strategy to model the separation of part of an economy and its inclusion into another country and applies this strategy to the case of Crimea, Ukraine, and Russia. Having constructed a model for the new geographical and economic situation, we reinvestigate the possible effects of a Deep and Comprehensive Free Trade Agreement between Ukraine and the EU and compare the results for the situation with Crimea as part of Ukraine. We find that the annexation of Crimea leads to severe economic losses for Ukraine which are partly overproportional compared to Crimea's economic size. These negative effects can be compensated by implementing the DCFTA with the EU as we also show in our model results.     

Expected inflation, expected stock returns, and money illusion: What can we learn from survey expectations?

We show empirically that survey-based measures of expected inflation are significant and strong predictors of future aggregate stock returns in several industrialized countries both in-sample and out-of-sample. Empirically discriminating between competing sources of this return predictability by virtue of a comprehensive set of expectations data, we find that money illusion seems to be the driving force behind our results. Another popular hypothesis – inflation as a proxy for aggregate risk aversion – is not supported by thedata.     

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.     

What can econophysics contribute to financial economics?

Econophysics presents itself as a new paradigm and a new specialty (or even a discipline), using various models and concepts imported from condensed matter and statistical physics to analyze financial phenomena. Financial economics is becoming more and more concerned by the emergence of econophysics because this new field deals with the economic reality. In this perspective, one might ask “What can econophysics contribute to financial economics?” After emphasizing the main differences between financial economics and econophysics, this paper will show that these two disciplines can be complementary. I then provide some research themes from econophysics that could be a source of inspiration for financial economists to broaden their theoretical framework.     

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.     

Do FOMC forecasts add value to staff forecasts?

This paper compares the economic forecasts of members of the Board of Governors and presidents of the Federal Reserve Banks, and then investigates the value of each group's forecasts in supplementing the forecasts of the Board of Governors' staff. We find that the presidents tend to forecast higher inflation and real GDP growth, and lower unemployment than the members of the Board of Governors. We also find that the presidents' real GDP and unemployment rate forecasts add value to the real economy forecasts of the staff, while the governors' inflation forecasts add value to the staff's inflation forecasts.     

What can Remove the Obstacles from the Process of Asian Unification

Presently, the regional economic cooperation in Asia is developing fast and well with the ASEAN as an axis and with the proactive participation of major Asian nations such as China, 3apan, Korea and India. While envisaging the bright prospect, the unification process, however, is destined to encounter some obstacles and difficulties. By analyzing the hindrance, as well the reasons why Asia lags far behind Europe in unification, the author believes that Asian nations should draw on the lessons and experiences of European countries and learn their principle of subsidiary （bottom-up approaches）, which may serve as the key solution for Asia to overcome the impending obstructions.     

The random walk versus unbiased efficiency: can we separate the wheat from the chaff?

Abstract:

In the issue under investigation the wheat cannot be separated from the chaff because all we have is chaff. The random walk and unbiased efficiency are equally bad forecasters that should not be used as benchmarks for measuring forecasting accuracy. The simulation and econometric results show that when two forecasters are not independent they produce forecasts of similar quality, in which case it is erroneous to use the forward rate as a forecaster and the spot rate as a benchmark. Theoretical and intuitive explanations are presented for why the random walk and unbiased efficiency produce poor-quality forecasts that are almost identical. The failure of unbiased efficiency is explained primarily in terms of the post Keynesian view of the forward exchange rate.