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This study aims to investigate, for the first time in the literature, the stochastic properties of the US aggregate health-care price inflation rate series, using the data on health-care inflation rates for a panel of 17 major US urban areas for the period 1966-2006.

This goal is undertaken by applying the first- and second-generation panel unit root tests and the panel stationary test developed recently by Carrion-i-Silvestre et al. (2005) that allows for endogenously determined multiple structural breaks and is flexible enough to control for the presence of cross-sectional dependence.

The empirical findings indicate that after controlling for the presence of cross-sectional dependence, finite sample bias, and asymptotic normality, the US aggregate health-care price inflation rate series can be characterized as a non-stationary process and not as a regime-wise stationary innovation process.

The research findings apply to understanding of health-care sector price escalation in US urban areas. These findings have timely implications for the understanding of the data structure and, therefore, constructs of economic models of urban health-care price inflation rates. The results confirming the presence of a unit root indicating a high degree of inflationary persistence in the health sector suggests need for further studies on health-care inflation rate persistence using the alternative measures of persistence. This study’s conclusions do not apply to non-urban areas.

The mean and variance of US urban health-care inflation rate are not constant. Therefore, insurers and policy rate setters need good understanding of the interplay of the various factors driving the explosive health-care insurance rates over the large US metropolitan landscape. The study findings have implications for health-care insurance premium rate setting, health-care inflation econometric modeling and forecasting.

Payers (private and public employers) of health-care insurance rates in US urban areas should evaluate the value of benefits received in relation to the skyrocketing rise of health-care insurance premiums.

This is the first empirical research focusing on the shape of urban health-care inflation rates in the USA.

From the standpoint of a policy maker who has access to a number of expert forecasts, the uncertainty of a combined or ensemble forecast should be interpreted as that of a typical forecaster randomly drawn from the pool. This uncertainty formula should incorporate forecaster discord, as justified by (i) disagreement as a component of combined forecast uncertainty, (ii) the model averaging literature, and (iii) central banks’ communication of uncertainty via fan charts. Using new statistics to test for the homogeneity of idiosyncratic errors under the joint limits with both T and n approaching infinity simultaneously, the authors find that some previously used measures can significantly underestimate the conceptually correct benchmark forecast uncertainty.

The purpose of this study is to seek to re-examine the threshold effects of public debt on economic growth in Africa.

This study applies panel smooth transition regression approach advanced by González et al. (2017). The method allows for both heterogeneity as well as a smooth change of regression coefficients from one regime to another.

A debt threshold in the range of 62–66% is estimated for the whole sample. Low debt is found to be growth neutral but higher public debt is growth detrimental. For middle-income and resource-intensive countries, a debt threshold in the range of 58–63% is estimated. As part of robustness checks, a dynamic panel threshold model was also applied to deal with the endogeneity of debt, and a much higher debt threshold was estimated, at 74.3%. While low public debt is found to be either growth neutral or growth enhancing, high public debt is consistently detrimental to growth.

The findings of this study show that there is no single debt threshold applicable to all African countries, and confirm that the debt threshold level is sensitive to modeling choices. While further analysis is still needed to suggest a policy, the findings of this study show that high debt is detrimental to growth.

The novelty of this study is twofold. Contrary to previous studies on Africa, this study applies a different estimation technique which allows for heterogeneity and a smooth change of regression coefficients from one regime to another. Another novelty distinct from the previous studies is that, for robustness checks, this study divides the sample into low- and middle-income countries, and into resource- and nonresource intensive countries, as debt experience can differ among country groups. Further, as part of robustness checks, another estimation method is also applied in which the threshold variable (debt) is allowed to be endogenous.

This study aims to achieve three objectives: to explore the perception of consumers about supersized foods (in both pre- and post-consumption scenarios), to identify why consumers prefer supersized options over other available options and to determine the types of situations that push consumers to make such decisions.

This qualitative study uses the triangulation of projective methods, coupled with semi-structured interviews with 120 participants. The data was collected from major cities of Pakistan, using a convenient sample of 25 semi-structured interviews, 35 narratives and 60 sentence completions and constructions analyzed by performing thematic analysis.

The findings indicate that the antecedents of the purchase of supersized food include price/quantity trade-off, hunger, liking and the social setting of consumption. Such purchase decisions also lead to consequences such as saving after purchase, health concerns, food waste, guilt and satisfaction. The findings also reveal the factors that play a dual role of an antecedent and a consequence: sharing, social status, quantity and leisure time.

The knowledge of factors that make consumers select supersized foods can help marketers design deals that can control overconsumption and food waste. Instead of only focusing on the motivations behind the purchase of supersized foods, the authors also discuss the aspects of food purchase and consumption.

This study advances the literature on purchase decision, consumption and post-consumption of supersized foods, providing insights for food retailers, regulators and policymakers.

¿Cuándo y por qué los consumidores eligen alimentos de gran tamaño?

Este estudio busca alcanzar tres objetivos: 1) explorar la percepción de los consumidores sobre los alimentos de gran tamaño (tanto en escenarios previos como posteriores al consumo), 2) identificar por qué los consumidores prefieren las opciones de gran tamaño sobre otras opciones disponibles, y 3) determinar qué tipo de situaciones empujan a los consumidores a tomar tales decisiones.

Este estudio cualitativo emplea la triangulación de métodos proyectivos, junto con entrevistas semiestructuradas con 120 participantes. Los datos se recopilaron en las principales ciudades de Pakistán, utilizando una muestra conveniente de 25 entrevistas semiestructuradas, 35 narraciones y 60 terminaciones y construcciones de frases analizadas mediante la realización de un análisis temático.

Los resultados indican que los antecedentes de la compra de alimentos de gran tamaño incluyen la relación precio/cantidad, el hambre, el gusto y el entorno social del consumo. Estas decisiones de compra también conllevan consecuencias como el ahorro después de la compra, la preocupación por la salud, el desperdicio de alimentos, el sentimiento de culpa y la satisfacción. Los resultados también revelan los factores que desempeñan un doble papel de antecedente y consecuencia: compartir, estatus social, cantidad y tiempo de ocio.

El conocimiento de los factores que hacen que los consumidores seleccionen alimentos de gran tamaño puede ayudar a los responsables de marketing a diseñar ofertas que puedan controlar el consumo excesivo y el desperdicio de alimentos. En lugar de centrarse únicamente en las motivaciones que subyacen a la compra de alimentos de mayor tamaño, los autores también analizan los aspectos de la compra y el consumo de alimentos.

Este estudio supone un avance en la literatura sobre la decisión de compra, el consumo y el posconsumo de los alimentos de gran tamaño, proporcionando información a los minoristas de alimentos, a los reguladores y a los responsables políticos.

Gran tamaño, Alimentos de gran tamaño, Consumo de alimentos, Estudio cualitativo, Técnicas proyectivas

Investigación

消费者何时以及为何选择超大号食品？

本研究旨在实现三个目标。1）探索消费者对超大号食品的认知看法（在消费前和消费后的场景下）, 2）确定消费者为什么喜欢超大号食品而不是其他现有选择, 以及3）确定促使消费者做出这种决定的情况类型。

这项定性研究采用了投射方法中的的三角测量, 以及对120名参与者的半结构化访谈。这些数据是从巴基斯坦的主要城市收集的, 研究者使用了一个方便性样本, 其中包括25个半结构式访谈, 35个叙述, 以及60个句子的完成和结构。这些数据通过主题分析来进行解析。

研究结果表明, 购买超大号食品的前因包括价格/数量的权衡、饥饿感、喜好和消费的社会环境。这样的购买决定也导致了购买后的节省、健康问题、食物浪费、内疚和满足感等后果。研究结果还揭示了几个即是前因又是结果的双角色因素：分享、社会地位、数量和休闲时间。

了解促使消费者选择超大号食品的因素可以帮助营销人员设计能够控制过度消费和食品浪费的交易。作者不仅仅关注了购买超大号食品背后的动机, 还讨论了食品购买和消费的各个方面。

这项研究推进了关于超大食品的购买决策、消费和消费后的文献, 为食品零售商、监管者和政策制定者提供了见解。

关键词 超大, 超大食品, 食品消费, 定性研究, 投射技术

文章类型： 研究型论文

This paper aims to test three hypotheses in city growth literature documenting the poverty reduction observed in Brazil and exploring a rich spatial dataset for 5,564 Brazilian cities observed between 1991 and 2010. The large sample and the author's improved econometric methods allows one to better understand and measure how important income growth is for poverty reduction, the patterns of agglomeration and population growth in all Brazilian cities.

The author identifies literature gaps and use a sizeable spatial dataset for 5,564 Brazilian cities observed in 1991, 2000 and 2010 applying instrumental variables methods. The bias-corrected accelerated bootstrap percentile interval supports the author's point estimates.

This manuscript finds that Brazilian data for cities does not support Gibrat's law, raising the scope for urban planning and associated policies. Second, economic growth on a sustainable basis is still a vital source of poverty reduction (The author estimates the poverty elasticity at four percentage points). Lastly, agglomeration effects positively affect the city's productivity, while negative externalities underlie the city's development patterns.

Data for cities in Brazil possess unique characteristics such as spatial autocorrelation and endogeneity. Applying proper methods to find more reliable answers to the above three questions is a desirable procedure that must be encouraged. As the author points out in the manuscript, dealing with endogenous regressors in regional economics is still a developing matter that regional scientists could more generally apply to many regional issues.

This study reexamines the sustainability of fiscal policy in Sweden.

To test the sustainability of fiscal policy, two approaches are used; the methodology of Kejriwal and Perron (2010), testing for multiple structural changes in a cointegrated regression model and time-varying cointegration test of Bierens and Martins (2010), and Martins (2015).

Using the first approach of testing for multiple structural changes in a cointegrated regression model, the results indicate that government spending and revenue are cointegrated with two breaks. An estimation of a two-break long-run model shows that the slope coefficient increases from 0.678 to 0.892 from the first to the second regime, implying that fiscal deficits were weakly sustainable in the first two regimes, from 1800 to 1943, and from 1944 to 1974. Further, results from time-varying cointegration test indicate that cointegration between spending and revenue in Sweden is time-varying. Fiscal deficits were found to be unsustainable for the periods 1801–1811, 1831–1838, 1853–1860 , 1872–1882, 1897–1902, 1929–1940 and 1976–1982 and weakly sustainable over the rest of the study period.

A number of implications arise from this study: (1) Accounting for breaks in cointegration analysis and in the estimation of the level relationship between spending and revenue is very important because ignoring breaks may lead to an overestimated slope coefficient and hence a bias on the magnitude of fiscal deficit sustainability. (2) In testing for cointegration between spending and revenue, assuming a constant cointegrating slope when it is actually time-varying can also be misleading because deficits can be sustainable for a period of time and unsustainable over another period.

The contribution of this study is three-fold; first, the study uses a long series of annual data spanning over a period of two centuries, from 1800 to 2011. Second, because of the importance of structural change in economics, to examine the existence of a level relationship between spending and revenue, the study uses the methodology of Kejriwal and Perron (2010) to test for multiple structural changes in a cointegrated regression model, as well as time-varying cointegration of Bierens and Martins (2010) and Martins (2015).

Our main purpose is to test the unemployment invariance hypothesis in Italy.

This paper provides an empirical investigation of the unemployment and labor force participation in Italy.

Cointegration analysis results strongly suggest a clear long-run relationship between unemployment and labor force participation revealing a persistent and general added worker effect.

Our results seem to confute the unemployment invariance hypothesis.

The author analyzes households' inflation expectations data for India, collected quarterly by the RBI for more than a decade. The contribution of this paper lies in two folds. First, this study examines the relationship between relatively recent inflation expectations survey of households (IESH) and the actual inflation for India. Secondly, the author employs a structural VAR with the time period 2006 Q2 to 2020 Q2 on inflation expectation survey data of India. A short-term non-recursive restriction is imposed in the model in order to capture the simultaneous co-dependence causal effect of inflation expectation and realized inflation.

This paper studies the dynamic behavior of inflation expectations survey data in two folds. First, the author analyzes the time series property of the survey data. The author begins with testing the stationarity property of the series, followed by the casual relationship between the expected and actual inflation. The author further examines the short-run and long-run behavior of the IESH with actual inflation. Employing autoregressive distributed lag and Johansen co-integration, the author tested if a long-run relationship exists between the variables. In the second approach, the author investigates the determinants of inflation expectations by employing a non-recursive SVAR model.

The preliminary explanatory test reveals that inflation expectation is a policy variable and should be used in monetary policy as an instrument variable. The model identifies the price puzzle for India. The author finds that the response of inflation to a monetary policy shock is neutral. The results also indicate that the expectations of the general public are self-fulfilling.

IESH has only commenced from September 2005, hence is relatively new as compared to other survey in developed countries. Being a new data set so far, the author could not locate any study devoted in analyzing the behavior of the data with other macroeconomic variables.