Cost Analysis of Calcium in Store Brand versus National Brand Grocery Products

Objective: This study was to determine if calcium fortification yields a higher price per serving in grocery store products. Researchers compared store brand to national brand grocery products in relation to cost in order to examine if calcium values were similar between store brand and national brand products. Methods: A total of 112 store brand and 211 national brand grocery products were collected from three low (national chain store), middle and high priced (Virginia and North Carolina regional store) grocery venues. Products were compared using price and calcium percentage per serving. ANOVA was used to determine between store brand and national brand for price per serving and calcium content, and between grocery venues. Results: National brand fortified products had a significantly lower mean price per serving when compared to national brand non-fortified products (p = 0.0002). There was no statistical difference between store brand fortified and non-fortified products (p = 0.9256). Low priced store brand products had the lowest mean price per serving ($0.34 ±0.24). Conclusions: This study found store brand products have similar calcium content as national brand products. Product cost was lower at low priced store compared to middle and high priced stores.     

Financial development,economic growth and convergence clubs

To study the role of financial development in economic growth, we apply an array of convergence tests designed to capture nonlinear transitional dynamics to real outputs per capita. Strong evidence of multiple convergence clubs is observed, implying that the clubs are formed based on the initial level of real output per capita and average growth rate. Our empirical results show that the stage of economic growth of each country plays an important role for the composition of the convergence clubs. Furthermore, financial development emerges to be a significant determinant, albeit plays differently in the economic growth of each convergence club.     

How Fast are Semiconductor Prices Falling?

The Producer Price Index (PPI) for the U.S. suggests that semiconductor prices have barely been falling in recent years, a dramatic contrast to the rapid declines reported from the mid‐1980s to the early 2000s. This slowdown in the rate of decline is puzzling in light of evidence that the performance of microprocessor units (MPUs) has continued to improve at a rapid pace. Over the course of the 2000s, the MPU prices posted by Intel, the dominant producer of MPUs, became much stickier over the chips' life cycle. As a result of this change, we argue that the matched‐model methodology used in the PPI for MPUs likely started to be biased after the early 2000s and that hedonic indexes can provide a more accurate measure of price change since then. MPU prices fell rapidly through 2004 on every price measure we present, with the PPI declining at an even quicker pace than the hedonic indexes. However, from 2004 to 2009, our preferred hedonic index fell faster than the PPI, and from 2009 to 2013 the gap widened further, with our preferred index falling at an average annual rate of 42 percent, while the PPI declined at only a 6 percent rate. Given that MPUs currently represent about half of U.S. shipments of semiconductors, this difference has important implications for gauging the rate of innovation in the semiconductor sector.     

Forecasting using heterogeneous panels with cross-sectional dependence

In this paper, we focus on forecasting methods that use heterogeneous panels in the presence of cross-sectional dependence in terms of both spatial error dependence and common factors. We propose two main approaches to estimating the factor structure: a residuals-based approach, and an approach that uses a panel of auxiliary variables to extract the factors. Small sample properties of the proposed methods are investigated through Monte Carlo simulations and applied to predict house price inflation in OECD countries.     

The role of text-extracted investor sentiment in Chinese stock price prediction with the enhancement of deep learning

Whether investor sentiment affects stock prices is an issue of long-standing interest for economists. We conduct a comprehensive study of the predictability of investor sentiment, which is measured directly by extracting expectations from online user-generated content (UGC) on the stock message board of Eastmoney.com in the Chinese stock market. We consider the influential factors in prediction, including the selections of different text classification algorithms, price forecasting models, time horizons, and information update schemes. Using comparisons of the long short-term memory (LSTM) model, logistic regression, support vector machine, and Naïve Bayes model, the results show that daily investor sentiment contains predictive information only for open prices, while the hourly sentiment has two hours of leading predictability for closing prices. Investors do update their expectations during trading hours. Moreover, our results reveal that advanced models, such as LSTM, can provide more predictive power with investor sentiment only if the inputs of a model contain predictive information.     

Fiscal and monetary interdependence

Where classical economics integrates the quantity theory of money with the concept of Ricardian equivalence, the tendency of recent macroeconomic presentations is to focus either upon money and inflation or upon taxation and debt. That neglect of classical monetary–fiscal integration is surprising, given an initiative by the International Monetary Fund that set credit, money, and fiscal policy within a single structure. This article places those ‘credit counterparts of broad money’ in the context of the Great Depression and the recent global financial crisis. The upshot is a set of conclusions: that, to counter the prospect of deflation, quantitative easing is a weak policy response; that fiscal deficits are better; and that cuts in taxation are preferable to increased government spending.     

Credit risk pricing and the rationality of lending decision-making within dual banking systems: A parametric approach

The reduction of non-performing loans, and making correct provisions for them, plays a primary role in the management and minimization of banking credit risk. However, these actions depend primarily upon the cost at which banks may dispose of these bad loans. Hence, this study aims to perceive the price of banks’ credit risk via estimating the shadow price of non-performing loans. We assess and compare the perceived price of the credit risk of Islamic and conventional banks operating in 9 countries from the Middle East and Asia, using a quadratic directional distance function. Following this, we evaluate the impact of different settings of directional vectors on shadow prices by conducting a risk-sensitivity analysis. Applying bootstrap regression, the factors affecting NPLs’ prices are further investigated. The paper concludes that the estimation of the shadow prices of bad loans can provide important elements in favor of credit risk management and, therefore, credit risk mitigation.     

Can governance help in making an IPO “successful”? New evidence from Europe

This paper investigates the determinants of a “successful” IPO from a corporate governance perspective upon a representative sample of European listings from 2000 to 2015. We use an extensive dataset of market performance, financial data, and corporate governance characteristics to run the investigation. Differently from previous studies, our analysis embraces both a short‐term perspective and a medium–long‐term perspective, where the board of directors seems to perform different tasks, moving from a value creation to a value protection strategy. Among the others, we find that board size, board independence, and their qualifications, together with their experience in other boards, are associated with a positive performance of the IPO in a short‐term horizon and in the medium–long‐term period, although significant differences emerge among those time perspectives.     

Environmental policies,national culture,and stock price crash risk: Evidence from renewable energy firms

This study investigates the impact of country‐level environmental performance and national culture on the stock price crash risk of renewable energy firms. Employing a large sample of 626 renewable energy firms across 31 countries, we find a significant nonlinear relationship between country‐level environmental performance and crash risk. National culture dimensions are found to strongly predict the crash risk of renewable energy firms, particularly after the global financial crisis. On the contrary, national culture dimensions and environmental policies are observed to not exert any significance in explaining the crash risk of fossil fuel firms. Our results are robust with respect to alternative measures of stock price crash risk and the endogeneity of national culture dimensions. Overall, the findings of this paper contribute to the environmental economics literature by providing new evidence regarding the role of societal and environmental factors in explaining the stock price crash risk of energy firms.     

化肥价格变化对粮食价格的影响研究--基于省际动态面板数据模型的系统GMM检验

基于我国粮食价格与化肥价格变动趋势的分析,运用2006年~2017年省际动态面板数据模型和系统GMM方法,实证检验了化肥价格变动对粮食价格的影响。结果表明:化肥价格变动对粮食价格存在显著的正向影响,在考虑化肥价格影响下,农业生产服务、种子等农资价格对粮食价格也存在显著的正向影响,机械化农具和农药价格对粮食价格不显著,"价补分离"政策对粮食价格存在显著负向影响。因此,在化肥减量行动背景下,适度调控化肥价格,避免化肥价格上升挤占粮农利润,大力发展农业生产性服务业和种子业,继续实行"价补分离"政策,提高补贴精准性,减少农民投入成本。