Latent social distancing: Identification,causes and consequences

It is not directly observable how effectively a society practices social distancing during the COVID-19 pandemic. This paper proposes a novel and robust methodology to identify latent social distancing at the country level. We extend the Susceptible-Exposed-Infectious-Recovered-Deceased (SEIRD) model with a time-varying, country-specific distancing term, and derive the Model-Inferred DIStancing index (MIDIS) for 120 countries using readily available epidemiological data. The index is not sensitive to measurement errors in epidemiological data and to the values assigned to model parameters. The evolution of MIDIS shows that countries exhibit diverse patterns of distancing during the first wave of the COVID-19 pandemic—a persistent increase, a trendless fluctuation, and an inverted U are among these patterns. We then implement regression analyses using MIDIS and obtain the following results: First, MIDIS is strongly correlated with available mobility statistics, at least for high income countries. Second, MIDIS is also strongly associated with (i) the stringency of lockdown measures (governmental response), (ii) the cumulative number of deceased persons (behavioral response), and (iii) the time that passed since the first confirmed case (temporal response). Third, there is statistically significant regional variation in MIDIS, and more developed societies achieve higher distancing levels. Finally, MIDIS is used to explain output losses experienced during the pandemic, and it is shown that there is a robust positive relationship between the two, with sizable economic effects.     

Learning and time-varying macroeconomic volatility

This paper presents a DSGE model in which agents׳ learning about the economy can endogenously generate time-varying macroeconomic volatility. Economic agents use simple models to form expectations and need to learn the relevant parameters. Their gain coefficient is endogenous and is adjusted according to past forecast errors.The model is estimated using likelihood-based Bayesian methods. The endogenous gain is jointly estimated with the structural parameters of the system.The estimation results show that private agents appear to have often switched to constant-gain learning, with a high constant gain, during most of the 1970s and until the early 1980s, while reverting to a decreasing gain later on. As a result, the model can generate a pattern of volatility, which is increasing in the 1970s and falling in the second half of the sample, with a decline that can roughly match the magnitude of the so-called “Great Moderation” in the 1984–2007 period. The paper also documents how a failure to incorporate learning into the estimation may lead econometricians to spuriously find time-varying volatility in the exogenous shocks, even when these have constant variance by construction.     

Learning, monetary policy rules, and macroeconomic stability

Several papers have documented a regime switch in US monetary policy from ‘passive’ and destabilizing in the pre-1979 period to ‘active’ and stabilizing afterwards. These studies typically work with DSGE models with rational expectations.This paper relaxes the assumption of rational expectations and allows for learning instead. Economic agents form expectations from simple models and update the parameters through constant-gain learning. In this setting, the paper aims to test whether monetary policy may have been a source of macroeconomic instability in the 1970s by inducing unstable learning dynamics.The model is estimated by Bayesian methods. The constant-gain coefficient is jointly estimated with the structural and policy parameters in the system.The results show that monetary policy was respecting the Taylor principle also in the pre-1979 period and, therefore, did not trigger macroeconomic instability.     

One model and various experts: Evaluating Dutch macroeconomic forecasts

The Netherlands Bureau for Economic Policy Analysis (CPB) uses a large macroeconomic model to create forecasts of various important macroeconomic variables. The outcomes of this model are usually filtered by experts, and it is the expert forecasts that are made available to the general public. In this paper we re-create the model forecasts for the period 1997-2008 and compare the expert forecasts with the pure model forecasts. Our key findings from the first time that this unique database has been analyzed are that (i) experts adjust upwards more often; (ii) expert adjustments are not autocorrelated, but their sizes do depend on the value of the model forecast; (iii) the CPB model forecasts are biased for a range of variables, but (iv) at the same time, the associated expert forecasts are more often unbiased; and that (v) expert forecasts are far more accurate than the model forecasts, particularly when the forecast horizon is short. In summary, the final CPB forecasts de-bias the model forecasts and lead to higher accuracies than the initial model forecasts.     

Reprint to: Infrastructure provision and macroeconomic performance

This paper studies the differences between private and government provision of infrastructure. Capital utilization decisions and their differential role in determining market prices for capital goods under the two regimes of infrastructure provision serve as a critical transmission mechanism for fiscal policy. A subsidy to private providers of infrastructure is preferable to direct government provision irrespective of how the subsidy or expenditure is financed. The case for private provision is much stronger in economies characterized by high levels of congestion. The choice between private and government provision also has a crucial effect on the design of optimal fiscal policy.     

Infrastructure provision and macroeconomic performance

This paper studies the differences between private and government provision of infrastructure. Capital utilization decisions and their differential role in determining market prices for capital goods under the two regimes of infrastructure provision serve as a critical transmission mechanism for fiscal policy. A subsidy to private providers of infrastructure is preferable to direct government provision irrespective of how the subsidy or expenditure is financed. The case for private provision is much stronger in economies characterized by high levels of congestion. The choice between private and government provision also has a crucial effect on the design of optimal fiscal policy.     

Macroeconomic Adjustment and the Poor: Analytical Issues and Cross‐Country Evidence

Abstract.  This paper studies the links between macroeconomic adjustment and poverty. The first part summarizes some of the recent evidence on poverty in the developing world. The second reviews the various channels through which macroeconomic policies affect the poor, whereas the third is devoted to the specific role of the labor market. It presents an analytical framework that captures some of the main features of the urban labor market in developing countries and studies the effects of fiscal adjustment on wages, employment, and poverty. The fourth part presents cross‐country regressions linking various macroeconomic and structural variables to poverty. Higher levels and growth rates of per capita income, higher rates of real exchange rate depreciation, better health conditions, and a greater degree of commercial openness lower poverty, whereas inflation, greater income inequality, and macroeconomic volatility tend to increase it. Moreover, the impact of growth on poverty appears to be asymmetric; it seems to result from a significant relationship between episodes of increasing poverty and negative growth rates.     

Accuracy, unbiasedness and efficiency of professional macroeconomic forecasts: An empirical comparison for the G7

In this paper, we use survey data to analyze the accuracy, unbiasedness and efficiency of professional macroeconomic forecasts. We analyze a large panel of individual forecasts that has not previously been analyzed in the literature. We provide evidence on the properties of forecasts for all G7-countries and for four different macroeconomic variables. Our results show a high degree of dispersion of forecast accuracy across forecasters. We also find that there are large differences in the performances of forecasters, not only across countries but also across different macroeconomic variables. In general, the forecasts tend to be biased in situations where the forecasters have to learn about large structural shocks or gradual changes in the trend of a variable. Furthermore, while a sizable fraction of forecasters seem to smooth their GDP forecasts significantly, this does not apply to forecasts made for other macroeconomic variables.     

EQUALITY OF OPPORTUNITY: POLICY AND MEASUREMENT PARADIGMS

Abstract Equality of opportunity is a widely accepted principle of distributive justice and it is the leading idea of most political platforms in several countries. According to this principle, a society might institute policies that secure an equal distribution of the means to reach a valuable outcome among its members. Once the set of opportunities have been equalized, which particular opportunity, the individual chooses from those open to her, is outside the scope of justice. Ex ante inequalities, and only those inequalities, should be eliminated or compensated for by public intervention. The recent literature on the opportunity egalitarianism often merges these questions introducing two different economic issues. On one side the design of a public policy intended to implement the equality of opportunity view and on the other side the problem of measuring the degree of opportunity inequality in a society. We describe the basic setting and assumptions of some different approaches derived by Roemer’s algorithm for public policy and then we discuss some theoretical and empirical studies to separate and test alternative paradigms on the measurement of inequality of opportunity. Accordingly, an extended critique on the causality issue on policies and measurements is taken into account.     

Forecasting China's foreign exchange reserves using dynamic model averaging: The roles of macroeconomic fundamentals,financial stress and economic uncertainty

We develop models for examining possible predictors of growth of China's foreign exchange reserves that embrace Chinese and global trade, financial and risk (uncertainty) factors. Specifically, by comparing with other alternative models, we show that the dynamic model averaging (DMA) and dynamic model selection (DMS) models outperform not only linear models (such as random walk, recursive OLS-AR(1) models, recursive OLS with all predictive variables models) but also the Bayesian model averaging (BMA) model for examining possible predictors of growth of those reserves. The DMS is the best overall across all forecast horizons. While some predictors matter more than others over the forecast horizons, there are few that stand the test of time. The US–China interest rate differential has a superior predictive power among the 13 predictors considered, followed by the nominal effective exchange rate and the interest rate spread for most of the forecast horizons. The relative predictive prowess of the oil and copper prices alternates, depending on the commodity cycles. Policy implications are also provided.     

交通项目的公众参与社会评价——以安徽中等城市交通项目为例

论文以“安徽省中等城市交通项目”的公众参与社会评价为例,对该项目的经验进行归纳.首先,识别了项目的利益相关者,主要包括业主及项目设计和施工单位、交通相关的政府机构、公共交通运输部门和项目城市居民,其中,项目城市居民是最主要的受益者;其次,根据不同利益相关者的特点,分别采用了深度访谈、座谈会、问卷调查和绘制交通图等方法,以问题为导向,了解各市交通路网建设、基础设施、交通管理和交通安全存在的问题;第三,深入剖析发现问题的原因,积极与项目办、业主、设计单位展开协调和沟通,赋予各利益相关者参与项目设计的权利,特别是弱势群体需求的表达,来完善项目的设计和后续管理,提出了可融入项目设计的规避风险措施,即社     

Social networks and citizen election forecasting: The more friends the better

Most citizens correctly forecast which party will win a given election, and such forecasts usually have a higher level of accuracy than voter intention polls. How do citizens do it? We argue that social networks are a big part of the answer: much of what we know as citizens comes from our interactions with others. Previous research has considered only indirect characteristics of social networks when analyzing why citizens are good forecasters. We use a unique German survey and consider direct measures of social networks in order to explore their role in election forecasting. We find that three network characteristics –  size, political composition, and frequency of political discussion – are among the most important variables when predicting the accuracy of citizens’ election forecasts.     

Social innovation with open source software: User engagement and development challenges in India

A diverse range of innovative solutions based on Free-and-Open-Source Software (FOSS) have been developed for marginalized communities in developing countries. It has been suggested that such small-scale and home-grown solutions (e.g. mobile phone apps), usually championed by social enterprises (SEs), are more likely to introduce pro-poor change than infrastructure heavy ICT initiatives designed by state and other international actors. In the Indian context, FOSS-based social innovations (SIs) introduced by SEs are helping poor communities tackle previously thought-to-be unresolvable socio-economic problems. An interesting question, therefore, would be: in what ways is the SE model and approach uniquely equipped to develop FOSS-based SIs that deliver pro-poor change? The empirical component of the research attempts to shed light on this question by uncovering the nuts and bolts of the development methodology deployed by an SE during the coding and launch of an FOSS-based SI. Findings highlight the significant role of the founder's social vision; the challenges of accurately capturing and translating to software developers the nature and nuance of social problems; and, the incumbent issues in putting together a methodology that creates active user engagement throughout the software development process, overcoming difficult barriers such as language and culture.     

Social Change: Measurement and Theory*

Societal change, which takes a variety of directions and forms and in no way can be assimilated or reduced to a single dimension, is often accompanied by a perception of insufficient understanding and lack of control. There is a frustrated need for mastering complexity and instability, separating the voluntary from the involuntary, the intended from the unintended, opportunities from risks, getting to the real causes and dominating the uncertain implications of social change. Social change catches us unprepared and confused. In this context statistics are generally considered a fundamental instrument of knowledge, but also part of the problem! In the public debate and in the specialized literature, the ability to measure social phenomena through current statistics and indicators is increasingly questioned. Data-it is claimed-are lacking, particularly longitudinal data; their quality (accuracy, relevance, timeliness, comparability, etc.) should be improved; indicators do not provide early warning signals, policy performance evaluation, and a precise indication of outcomes. Statistics cannot be used as a reliable and timely basis for decision making by individuals, organizations, governments, and for understanding these decisions. In some cases, statistics have been accused of giving a misleading and false picture of reality: do we measure the real extent of social exclusion and unemployment? Do we fully capture the quality of life and the degradation of the environment? Mismeasurement has been deemed by some commentators as being responsible for the wrong focus in inflation and stabilization policies, science and technology, unemployment and poverty. The productivity paradox, the informal economy, failure to measure welfare and the quality of urban life are instances where statistics do not seem to provide complete and satisfactory answers to the demand for information and knowledge. Our paper illustrates how, quite independently of measurement techniques and data production processes, the inadequacy of the conceptual framework may explain mismeasurement in relation to complex (multidimensional) and dynamic social phenomena. It is then to social theories, explanations and interpretations that statisticians need to turn, in order to come to grips with the new challenges in social measurement. We will develop this thesis looking at a few cases where measurement issues can be connected to both theoretical and empirical difficulties. The statistical gap which reveals itself in the mismeasurement or difficult measurement of social phenomena is closely interconnected with the social science gap. Only close collaboration between statisticians and social scientists can bring about continuous advancement in social science and quality improvement in social statistics.     

Impact of Islamic banking development and major macroeconomic variables on economic growth for Islamic countries: Evidence from panel smooth transition models

This study examines the nonlinear relationship between Islamic banking development, major macroeconomic variables and economic growth in Islamic countries. Using the panel smooth transition model, the results show a positive nonlinear relationship between Islamic banking development and economic growth. Moreover, the relationship between the macroeconomic variables and economic growth is asymmetric and regime-dependent. Further, by using the dynamic panel quantile model, we show that for many cases the Islamic banking variables lead economic growth across the quantiles. More specifically, foreign direct investment, oil production and inflation have a positive impact on economic growth during the normal financial development state, while government consumption, one-lag economic growth, terms of trade and financial development have a negative impact on economic growth for this state. The human capital index, education and the rule of law have an insignificant impact, regardless of the prevailing regime. The results for the separated oil-importing and oil-exporting economies are generally consistent with the combined sample regarding the Islamic banking development variables. As for the macro variables, they have a positive and significant (insignificant) effect on EG for the oil-importing (oil-exporting) economies for almost all models.     

企业的社会责任——从营销战略创新角度看

为了实现企业与社会的和谐共赢,描述了企业社会责任的内涵,分析了21世纪企业社会责任的新趋势,企业承担社会责任的原因,以及企业承担社会责任的实践。理论分析和实例表明:承担社会责任的企业在产品营销方面获得了成功,证明企业可以将承担社会责任作为一种新的市场营销手段。     

SESAME: an Integrated Economic and Social Accounting System

This article outlines a statistical information system that serves to monitor and analyze the interactions between economic development and social change. This so-called SESAME links the monetary data in the national accounts to non-monetary social and environmental data, and yields a consistent set of core indicators on the development of national welfare.     

Issues in New Political Economy: An Overview

A brief overview of the historical background, nature, and rapid growth in volume and scope of new political economy since the early 1980s is provided. the paper continues with some general reflections on the strengths and weaknesses of the new political economy approach, illustrated by the other contributions to this special issue of the Journal of Economic Surveys . The final Section summarises these contributions.     

Extending the SAM with Social and Environmental Indicators: An Application to Bolivia

Extending economic accounts with sets of social and environmental indicators is a first step towards a more integrated analysis of aspects of sustainability problems. In this article, therefore, a proposal is made to nest social and environmental indicators into an existing economic accounting framework. The Social Accounting Matrix (SAM) is taken as a basis, because of its flexibility regarding extensions with non-monetary data addressing social and environmental concerns. The main thrust of the paper is methodological. From the discussion of methodological issues and the application to the SAM for Bolivia for the year 1989, it is concluded that it is, in principle, feasible and relatively simple to extend the SAM with the two sets of indicators. However, additional data will have to be collected to be able to address, more adequately, the problems of sustainability.     

Coalitional games with veto players: Consistency, monotonicity and Nash outcomes

Following Dagan et al. [Dagan, N., Volij, O., Serrano, R. (1997). A non-cooperative view on consistent bankruptcy rules, Games Econ. Behav. 18, 55–72], we construct an extensive form game for veto-balanced TU games in which a veto player is the proposer and the other players are responders. The set of Nash outcomes of this extensive form game is described, and compared to solutions of TU games such as the nucleolus, kernel and egalitarian core. We find necessary and sufficient conditions under which the nucleolus of the game is a Nash outcome.