Structural Estimation and Solution of International Trade Models with Heterogeneous Firms

We present an empirical implementation of a general-equilibrium model of international trade with heterogeneous manufacturing firms. The theory underlying our model is consistent with Melitz (2003). A nonlinear structural estimation procedure identifies a set of core parameters and unobserved firm-level trade frictions that best fit the geographic pattern of trade. Once the parameters are identified, we utilize a decomposition technique for computing general-equilibrium counterfactuals. We illustrate this technique using trade and protection data from the Global Trade Analysis Project (GTAP). We first assess the economic effects of reductions in measured tariffs. Taking the simple-average welfare change across regions the Melitz structure indicates welfare gains from liberalization that are nearly four times larger than in a standard policy simulation model. Furthermore, when we compare the economic impact of tariffs with reductions in estimated fixed trade costs we find that policy measures affecting the fixed costs of firmentry are of greater importance than conventional tariff barriers.

Structural Estimation and Solution of International Trade Models with Heterogeneous Firms

We present an empirical implementation of a general-equilibrium model of international trade with heterogeneous manufacturing firms. The theory underlying our model is consistent with Melitz (2003). A nonlinear structural estimation procedure identifies a set of core parameters and unobserved firm-level trade frictions that best fit the geographic pattern of trade. Once the parameters are identified, we utilize a decomposition technique for computing general-equilibrium counterfactuals. We first assess the economic effects of reductions in measured tariffs. Taking the simple-average welfare change across regions the Melitz structure indicates welfare gains from liberalization that are nearly four times larger than in a standard trade policy simulation. Furthermore, when we compare the economic impact of tariff reductions with reductions in estimated fixed trade costs we find that policy measures affecting the fixed costs are of greater importance than tariff barriers

Trade and Welfare: Does Industrial Organization Matter?

Many contemporary theoretic studies of trade over geography reduce to an ex- amination of constant-elasticity reactions to changes in iceberg trade costs. These impacts are readily analyzed in simple constant-returns models based on the Arm- ington (1969) assumption of regionally differentiated goods. Following the line of reasoning suggested by Arkolakis et al. (2008) one can reach the surprising conclu- sion that industrial organization does not matter. In the present paper, we show that this finding is fragile, and with a minor elaboration of their model, the rich industrial-organization features of the popular Melitz (2003) model do, in fact, gen- erate important differences for trade and welfare.Variety effects, Heterogeneous firms, Gains from trade

Modeling services liberalization : the case of Kenya

This paper employs a 55 sector small open economy computable general equilibrium model of the Kenyan economy to assess the impact of the liberalization of regulatory barriers against foreign and domestic business service providers in Kenya. The model incorporates productivity effects in both goods and services markets endogenously, through a Dixit-Stiglitz framework. It estimates the ad valorem equivalent of barriers to foreign direct investment based on detailed questionnaires completed by specialists in Kenya. The authors estimate that Kenya will gain about 11 percent of the value of Kenyan consumption in the medium run (or about 10 percent of gross domestic product) from a full reform package that also includes uniform tariffs. The estimated gains increase to 77 percent of consumption in the long-run steady-state model, where the impact on the accumulation of capital from an improvement in the productivity of capital is taken into account. Decomposition exercises reveal that the largest gains to Kenya will derive from liberalization of costly regulatory barriers that are non-discriminatory in their impacts between Kenyan and multinational service providers.Transport Economics Policy&Planning,Economic Theory&Research,Banks&Banking Reform,Emerging Markets,Debt Markets

Carbon policy and the structure of global trade

Alternative perspectives on the structure of international trade have important implications for the evaluation of climate policy. In this paper we assess climate policy in the context of three important alternative trade formulations. First is a Heckscher-Ohlin model based on trade in homogeneous products, which establishes the traditional neoclassical view on comparative advantage. Second is an Armington model based on regionally differentiated goods, which constitutes a popular specification for numerical simulations of trade policy. Third is a Melitz model based on monopolistic-competition and firm heterogeneity. This heterogeneous-firms framework is adopted in many contemporary theoretic and empirical investigations in international trade. As we show in this paper, the three alternative trade formulations have important implications for the assessment of climate policy with respect to competitive effects for energy-intensive production (and hence carbon leakage) as well as the transmission of policy burdens across countries

Impact of revised CO2 growth projections for China on global stabilization goals

Recent growth in carbon dioxide emissions from China's energy sector has exceeded expectations. In a major US government study of future emissions released in 2007 (1), participating models appear to have substantially underestimated the near-term rate of increase in China's emissions. We present a recalibration of one of those models to be consistent with both current observations and historical development patterns. The implications of the new specification for the feasibility of commonly discussed stabilization targets, particularly when considering incomplete global participation, are profound. Unless China's emissions begin to depart soon from their (newly projected) business-as-usual path, stringent stabilization goals may be unattainable. The current round of global policy negotiations must engage China and other developing countries, not to the exclusion of emissions reductions in the developed world and possibly with the help of significant financial incentives, if such goals are to be achieved. It is in all nations' interests to work cooperatively to limit our interference with the global climate

Projections of epidemic transmission and estimation of vaccination impact during an ongoing Ebola virus disease outbreak in Northeastern Democratic Republic of Congo, as of Feb. 25, 2019.

BackgroundAs of February 25, 2019, 875 cases of Ebola virus disease (EVD) were reported in North Kivu and Ituri Provinces, Democratic Republic of Congo. Since the beginning of October 2018, the outbreak has largely shifted into regions in which active armed conflict has occurred, and in which EVD cases and their contacts have been difficult for health workers to reach. We used available data on the current outbreak, with case-count time series from prior outbreaks, to project the short-term and long-term course of the outbreak.MethodsFor short- and long-term projections, we modeled Ebola virus transmission using a stochastic branching process that assumes gradually quenching transmission rates estimated from past EVD outbreaks, with outbreak trajectories conditioned on agreement with the course of the current outbreak, and with multiple levels of vaccination coverage. We used two regression models to estimate similar projection periods. Short- and long-term projections were estimated using negative binomial autoregression and Theil-Sen regression, respectively. We also used Gott's rule to estimate a baseline minimum-information projection. We then constructed an ensemble of forecasts to be compared and recorded for future evaluation against final outcomes. From August 20, 2018 to February 25, 2019, short-term model projections were validated against known case counts.ResultsDuring validation of short-term projections, from one week to four weeks, we found models consistently scored higher on shorter-term forecasts. Based on case counts as of February 25, the stochastic model projected a median case count of 933 cases by February 18 (95% prediction interval: 872-1054) and 955 cases by March 4 (95% prediction interval: 874-1105), while the auto-regression model projects median case counts of 889 (95% prediction interval: 876-933) and 898 (95% prediction interval: 877-983) cases for those dates, respectively. Projected median final counts range from 953 to 1,749. Although the outbreak is already larger than all past Ebola outbreaks other than the 2013-2016 outbreak of over 26,000 cases, our models do not project that it is likely to grow to that scale. The stochastic model estimates that vaccination coverage in this outbreak is lower than reported in its trial setting in Sierra Leone.ConclusionsOur projections are concentrated in a range up to about 300 cases beyond those already reported. While a catastrophic outbreak is not projected, it is not ruled out, and prevention and vigilance are warranted. Prospective validation of our models in real time allowed us to generate more accurate short-term forecasts, and this process may prove useful for future real-time short-term forecasting. We estimate that transmission rates are higher than would be seen under target levels of 62% coverage due to contact tracing and vaccination, and this model estimate may offer a surrogate indicator for the outbreak response challenges

'Reclaiming the criminal' : the role and training of prison officers in England, 1877-1914

This article examines the role and training of prison officers in England, between 1877 and 1914. It is concerned with the changing penal philosophies and practices of this period and how these were implemented in local prisons, and the duties of the prison officer. More broadly, this article argues that the role of the prison officer and their training (from 1896) reflect wider ambiguities in prison policy and practice during this period

The mammalian phosphatidylinositol 3-phosphate 5-kinase (PIKfyve) regulates endosome-to-TGN retrograde transport

The yeast gene fab1 and its mammalian orthologue Pip5k3 encode the phosphatidylinositol 3-phosphate [PtdIns(3)P] 5-kinases Fab1p and PIKfyve, respectively, enzymes that generates phosphatidylinositol 3,5-bisphosphate [PtdIns(3,5)P(2)]. A shared feature of fab1Delta yeast cells and mammalian cells overexpressing a kinase-dead PIKfyve mutant is the formation of a swollen vacuolar phenotype: a phenotype that is suggestive of a conserved function for these enzymes and their product, PtdIns(3,5)P(2), in the regulation of endomembrane homeostasis. In the current study, fixed and live cell imaging has established that, when overexpressed at low levels in HeLa cells, PIKfyve is predominantly associated with dynamic tubular and vesicular elements of the early endosomal compartment. Moreover, through the use of small interfering RNA, it has been shown that suppression of PIKfyve induces the formation of swollen endosomal structures that maintain their early and late endosomal identity. Although internalisation, recycling and degradative sorting of receptors for epidermal growth factor and transferrin was unperturbed in PIKfyve suppressed cells, a clear defect in endosome to trans-Golgi-network (TGN) retrograde traffic was observed. These data argue that PIKfyve is predominantly associated with the early endosome, from where it regulates retrograde membrane trafficking to the TGN. It follows that the swollen endosomal phenotype observed in PIKfyve-suppressed cells results primarily from a reduction in retrograde membrane fission rather than a defect in multivesicular body biogenesis

Projections of Ebola outbreak size and duration with and without vaccine use in Équateur, Democratic Republic of Congo, as of May 27, 2018.

As of May 27, 2018, 6 suspected, 13 probable and 35 confirmed cases of Ebola virus disease (EVD) had been reported in Équateur Province, Democratic Republic of Congo. We used reported case counts and time series from prior outbreaks to estimate the total outbreak size and duration with and without vaccine use. We modeled Ebola virus transmission using a stochastic branching process model that included reproduction numbers from past Ebola outbreaks and a particle filtering method to generate a probabilistic projection of the outbreak size and duration conditioned on its reported trajectory to date; modeled using high (62%), low (44%), and zero (0%) estimates of vaccination coverage (after deployment). Additionally, we used the time series for 18 prior Ebola outbreaks from 1976 to 2016 to parameterize the Thiel-Sen regression model predicting the outbreak size from the number of observed cases from April 4 to May 27. We used these techniques on probable and confirmed case counts with and without inclusion of suspected cases. Probabilistic projections were scored against the actual outbreak size of 54 EVD cases, using a log-likelihood score. With the stochastic model, using high, low, and zero estimates of vaccination coverage, the median outbreak sizes for probable and confirmed cases were 82 cases (95% prediction interval [PI]: 55, 156), 104 cases (95% PI: 58, 271), and 213 cases (95% PI: 64, 1450), respectively. With the Thiel-Sen regression model, the median outbreak size was estimated to be 65.0 probable and confirmed cases (95% PI: 48.8, 119.7). Among our three mathematical models, the stochastic model with suspected cases and high vaccine coverage predicted total outbreak sizes closest to the true outcome. Relatively simple mathematical models updated in real time may inform outbreak response teams with projections of total outbreak size and duration