Economic contribution of essential air service flights on small and remote communities

The Essential Air Service Program (EAS) has attracted considerable criticism and has been a target for either modification or complete termination almost since its inception through the Airline Deregulation Act in 1978. Although its opponents emphasize the program's inefficiency, its supporters claim that the program is crucial to accessing small and remote communities, which helps them develop economically and socially. This paper demonstrates the economic contributions of EAS flights to small and remote communities. Using a two-stage least squares estimation, the major findings indicate that a 1% increase in air passenger traffic in EAS airports with a minimum annual air passenger traffic of 1000 likely leads to a 0.12% increase in per capita income of the community served by that airport. Our results also suggest that EAS communities that are able to sustain their subsidized flights experienced higher per capita income growth in the 1999–2011 period than did ex-EAS communities that lost their flights as a result of non-eligibility.     

Predictors of export performance in developing economies: a longitudinal analysis of Moroccan SMEs

Purpose: To help increase understanding of the export performance, we investigate the influence of firm size, research and development (R&D), advertising expenditures and network relationships, and develop a conceptual model to increase export intensity. Design/methodology/approach: The research involved a four-year longitudinal study of export performance of 168 exporting SMEs in Morocco (672 observations). The two-stage least square estimation (G2SLS) was used to test the hypotheses. Findings: The findings of the two-stage least square estimation (G2SLS) suggest that export sales and domestic sales are interdependent and influence each other. R&D expenditures and network affiliation have positive and significant impact on export sales, while advertising expenditure has a negative and significant influence on export sales. Research limitations/implications: Readers should use caution in generalizing the findings unless verified in other developing contexts. Practical implications: The findings of this study are useful for managers and export policy makers in developing countries. A proper understanding of the predictors of export performance may help them encourage the growth and diversification of exports that is so vital for developing countries. Originality/value: Export performance is a key element in the field of international marketing. Unfortunately, the literature exhibits a lack of empirical studies in developing countries, particularly in Maghreb regions. The empirical testing of the theoretical model in a developing economy is a significant contribution to fill the needed gap in the literature toward generalizing findings.     

Does the labor-income process contain a unit root? Evidence from individual-specific time series

Calibrations of models related to life-cycle behavior of consumption and saving often invoke the important assumption of a unit root in individuals׳ labor-income process. We for the first time test this assumption using methods for univariate time series. Based on longitudinal register data from 1968 to 2005, we first estimate an autoregressive model for each individual using a method for approximately median-unbiased estimation. We then exploit the resulting distribution of the individual-specific estimates to draw inference about the presence of a unit root. Results indicate that earnings for the representative worker are governed by a process where shocks to earnings have moderate persistence and are both economically and statistically significantly different from having permanent effects. These results question the heavy use of unit-root processes for earnings.     

Forecast combinations under structural break uncertainty

This paper proposes two new weighting schemes that average forecasts based on different estimation windows in order to account for possible structural change. The first scheme weights the forecasts according to the values of reversed ordered CUSUM (ROC) test statistics, while the second weighting method simply assigns heavier weights to forecasts that use more recent information. Simulation results show that, when structural breaks are present, forecasts based on the first weighting scheme outperform those based on a procedure that simply uses ROC tests to choose and forecast from a single post-break estimation window. Combination forecasts based on our second weighting scheme outperform equally weighted combination forecasts. An empirical application based on a NAIRU Phillips curve model for the G7 countries illustrates these findings, and also shows that combination forecasts can outperform the random walk forecasting model.     

The effects of public spending externalities

We conduct a positive analysis on the effects of ‘externalities’ produced by government spending. To this effect, we estimate, using U.S. data, an RBC model with two salient features. First, we allow government consumption to directly affect the marginal utility of consumption. Second, we allow public capital to shift the productivity of private factors. We provide an identification analysis that supports the strategy adopted for estimating the parameters governing these two channels. On one hand, private and government consumption are robustly estimated to be substitute goods. Because of substitutability, labor supply reacts little to a government consumption shock, so the estimated output multiplier is much lower than in models with separabilities. On the other hand, our results point towards public investment being ‘unproductive’.     

技术创新、金融创新与经济增长——基于中国省际面板数据

本文从实证分析层面对金融创新、技术创新与经济增长之间的作用关系进行探讨。基于我国 2000~2015 年省级面板数据，采用GMM估计方法，利用动态面板模型进行实证检验。结果表明：技术创新对经济增长的影响显著为正，单独的金融创新对经济增长起抑制作用，二者的交互作用则对经济增长起显著性正向作用。脱离实体经济的金融创新将抑制经济增长，也会间接阻碍技术创新对经济增长的影响。本文结合当前经济形势，从金融机构与创新企业相接轨共同提高创新水平、培养创新型人才等角度提出建议。     

Integrating partitioned prices via computational estimation

This paper introduces computational estimation to the literature on consumers’ numerical cognition. Computational estimation involves simplifying an arithmetic problem via mathematical procedures to produce an approximate answer. Employing calculation knowledge and approximation together, consumers are likely to use computational estimation as it is relatively accurate while saving cognitive effort compared to calculating values. Three studies applied to partitioned prices in the form of a base price and a percentage discount, demonstrate that when faced with this numeric integration task, the strategy consumers undertake is dependent on the characteristics of the numerals with discounts that are round or close to round being associated with greater use of computational estimation. Further, when employing computational estimation, consumers arrive at more accurate, and lower, price estimates in which they place more confidence than when using alternative an integration strategy. As a result, discounts that are near a round value are preferred to those that are not; a result that is dependent upon the use of computational estimation.     

Is ex-post credit risk affected by the cycles? The case of Italian banks

The objective of this research is to empirically examine if both credit and business cycle affect the ex-post credit risk (i.e. non-performing loans) in the banking system of Italy for the period 1995Q1–2014Q1. The increase in NPLs post-2008 has put into question the robustness of many European banks and the stability of the whole sector. It still remains a serious challenge, especially in Italy which is one of the countries that hit by the financial crisis. By employing fixed and random effects and a dynamic GMM estimation as econometric methodologies I find results that underline common causes for NPLs. Higher NPLs in Italy are mostly due to worse macroeconomic conditions (i.e. bad phase of business cycle) and due to excess credit. Through a Granger causality test, my arguments found even more support. Such findings can be helpful when designing macro-prudential as well as NPL resolution policies.     

Size,trend, and policy implications of the underground economy

We study the underground economy within a dynamic and stochastic general equilibrium framework. Our model combines limited tax enforcement with an otherwise standard two-sector neoclassical stochastic growth model. The Bayesian estimation of the model based on Italian data provides evidence in favor of an important underground sector in Italy, with a size that has increased steadily over the whole sample period. We show that this pattern is due to a steady increase in taxation. Fiscal policy experiments suggest that a moderate tax cut, along with a stronger effort in the monitoring process, causes a sizeable reduction in the size of the underground economy and provides a positive stimulus for the regular economy. Both of these effects jointly increase total fiscal revenues.     

DSGE pileups

The sampling distribution of estimators for DSGE structural parameters tends to be non-normal and/or pile up on the boundary of the theoretically admissible parameter space. This calls into question both the reliability of asymptotic approximations and the presumption of correct specification. This paper seeks to develop a conceptual framework for understanding how these phenomena arise, and to provide pragmatic methods for dealing with them in practice. The results are presented in three examples and a medium scale DSGE model.