Job Vacancy Chains and Local Employment Creation; the Case of Supply-Side Restrictions

The job-chains model of local labor market change is a demand-driven analytic device for estimating the effects of new job creation. This paper explores the effects of restricting supply, i.e. limiting job access, on the model’s primary outcomes: vacancy chain multipliers, welfare effects and distributional impacts. Major sources of labor supply are the local unemployed, out of the labor force and in-migrants. Three simulations are reported relating to 1) restricting new jobs to current local residents (i.e. no in-migrants), 2) restricting new jobs to current residents in the first round of hiring only and 3) restricting hiring to local unemployed/out of labor force on the first round alone. The results are compared to the basic model that assumes no supply-side restrictions. In terms of chain length, welfare effects, distributional impacts and policy palatability, first round restrictions on in-migrants would seem to be the most plausible option. However, as an economic development strategy,well targeted demand-side initiatives would still seem to be preferable.

Job vacancy chains in metropolitan labor markets

Metropolitan Labor markets are characterized by gross flows, much larger than the traditional net measures of employment change might suggest. Standard impact analyses of employment change tend to either ignore these flows or treat them as a matter of 'job churning'. But in a metropolitan area experiencing involuntary unemployment and underemployment, these flows may offer real opportunities for individuals to improve their employment positions. Such improvement occurs along 'job chains' in which a new vacancy opens a sequence of job changes allowing workers to move closer to their full employment wage. Not all chains are of the same length, nor does every chain produce the same welfare gain. This paper presents a model of job chaims which addresses chain length, welfare gains and distributional effects. The application of the model is illustrated using a hypothetical case of a new manufacturing firm in the Chicago metropolitan area. The job chains approach to estimating multiplier, efficiency and distributional effects associated with the firm, is compared with conventional impact analysis estimates. The conclusions discuss the implications of these estimates for the evaluation of local economic development projects.

What are Jobs Worth?

How much are jobs subsidized by state and local governments really worth? Policymakers have achieved surprisingly little consensus on the character and size of gains from economic development projects. Measurement of such gains must inevitably derive from a vision of the labor market. For subsidies to generate real gains for local workers, those workers must be unemployed or underemployed. Recent research on job chains provides a natural approach to such measurement issues. It addresses not only the number of job vacancies created as a result of a subsidized business investment o

Does Trickle Down Work?: Economic Development Strategies and Job Chains in Local Labor Markets

Persky, Felsenstein, and Carlson explore a new framework for evaluating state and local economic development efforts. They propose a method, referred to as the “job-chains approach,” that they say clarifies the potential justifications for economic development subsidies as well as the limitations surrounding these efforts. This innovative approach addresses not only the number of job vacancies created as a result of a subsidized business investment or expansion, but also the extent to which gains are achieved by the unemployed and the underemployed, whether skilled or unskilled.https://research.upjohn.org/up_press/1041/thumbnail.jp

Genotype Distribution and Sequence Variation of Hepatitis E Virus, Hong Kong

Most acute cases of infection with hepatitis E virus (HEV) in Hong Kong were autochthonous, sporadic, and occurred in older adults. All except 1 isolate belonged to genotype 4; most were phylogenetically related to swine isolates. The epidemiology is similar to that in industrialized countries, where zoonosis is the major source of HEV infection in humans

Inference of population splits and mixtures from genome-wide allele frequency data

Many aspects of the historical relationships between populations in a species are reflected in genetic data. Inferring these relationships from genetic data, however, remains a challenging task. In this paper, we present a statistical model for inferring the patterns of population splits and mixtures in multiple populations. In this model, the sampled populations in a species are related to their common ancestor through a graph of ancestral populations. Using genome-wide allele frequency data and a Gaussian approximation to genetic drift, we infer the structure of this graph. We applied this method to a set of 55 human populations and a set of 82 dog breeds and wild canids. In both species, we show that a simple bifurcating tree does not fully describe the data; in contrast, we infer many migration events. While some of the migration events that we find have been detected previously, many have not. For example, in the human data we infer that Cambodians trace approximately 16% of their ancestry to a population ancestral to other extant East Asian populations. In the dog data, we infer that both the boxer and basenji trace a considerable fraction of their ancestry (9% and 25%, respectively) to wolves subsequent to domestication, and that East Asian toy breeds (the Shih Tzu and the Pekingese) result from admixture between modern toy breeds and "ancient" Asian breeds. Software implementing the model described here, called TreeMix, is available at http://treemix.googlecode.comComment: 28 pages, 6 figures in main text. Attached supplement is 22 pages, 15 figures. This is an updated version of the preprint available at http://precedings.nature.com/documents/6956/version/

DNA Barcodes of Asian Houbara Bustard (Chlamydotis undulata macqueenii)

Populations of Houbara Bustards have dramatically declined in recent years. Captive breeding and reintroduction programs have had limited success in reviving population numbers and thus new technological solutions involving molecular methods are essential for the long term survival of this species. In this study, we sequenced the 694 bp segment of COI gene of the four specimens of Asian Houbara Bustard (Chlamydotis undulata macqueenii). We also compared these sequences with earlier published barcodes of 11 individuals comprising different families of the orders Gruiformes, Ciconiiformes, Podicipediformes and Crocodylia (out group). The pair-wise sequence comparison showed a total of 254 variable sites across all the 15 sequences from different taxa. Three of the four specimens of Houbara Bustard had an identical sequence of COI gene and one individual showed a single nucleotide difference (G > A transition at position 83). Within the bustard family (Otididae), comparison among the three species (Asian Houbara Bustard, Great Bustard (Otis tarda) and the Little Bustard (Tetrax tetrax)), representing three different genera, showed 116 variable sites. For another family (Rallidae), the intra-family variable sites among the individuals of four different genera were found to be 146. The COI genetic distances among the 15 individuals varied from 0.000 to 0.431. Phylogenetic analysis using 619 bp nucleotide segment of COI clearly discriminated all the species representing different genera, families and orders. All the four specimens of Houbara Bustard formed a single clade and are clearly separated from other two individuals of the same family (Otis tarda and Tetrax tetrax). The nucleotide sequence of partial segment of COI gene effectively discriminated the closely related species. This is the first study reporting the barcodes of Houbara Bustard and would be helpful in future molecular studies, particularly for the conservation of this threatened bird in Saudi Arabia

Comparative methods in R hackathon

The R statistical analysis package has emerged as a popular platform for implementation of powerful comparative methods to understand the evolution of organismal traits and diversification. A hackathon was organized to bring together active R developers as well as end-users working on the integration of comparative phylogenetic methods within R to actively address issues of data exchange standards, code interoperability, usability, documentation quality, and the breadth of functionality for comparative methods available within R. Outcomes included a new base package for phylogenetic trees and data, a public wiki with tutorials and overviews of existing packages, code to allow Mesquite and R to interact, improvement of existing packages, and increased interaction within the community

Robustness of Ancestral Sequence Reconstruction to Phylogenetic Uncertainty

Ancestral sequence reconstruction (ASR) is widely used to formulate and test hypotheses about the sequences, functions, and structures of ancient genes. Ancestral sequences are usually inferred from an alignment of extant sequences using a maximum likelihood (ML) phylogenetic algorithm, which calculates the most likely ancestral sequence assuming a probabilistic model of sequence evolution and a specific phylogeny—typically the tree with the ML. The true phylogeny is seldom known with certainty, however. ML methods ignore this uncertainty, whereas Bayesian methods incorporate it by integrating the likelihood of each ancestral state over a distribution of possible trees. It is not known whether Bayesian approaches to phylogenetic uncertainty improve the accuracy of inferred ancestral sequences. Here, we use simulation-based experiments under both simplified and empirically derived conditions to compare the accuracy of ASR carried out using ML and Bayesian approaches. We show that incorporating phylogenetic uncertainty by integrating over topologies very rarely changes the inferred ancestral state and does not improve the accuracy of the reconstructed ancestral sequence. Ancestral state reconstructions are robust to uncertainty about the underlying tree because the conditions that produce phylogenetic uncertainty also make the ancestral state identical across plausible trees; conversely, the conditions under which different phylogenies yield different inferred ancestral states produce little or no ambiguity about the true phylogeny. Our results suggest that ML can produce accurate ASRs, even in the face of phylogenetic uncertainty. Using Bayesian integration to incorporate this uncertainty is neither necessary nor beneficial