Alternative industrial development paths for Indonesia: SAM and CGE analyses

In this article, we examine the economy-wide effects of three alternative growth paths for Indonesia's industrial sector using SAM (social accounting matrix) multiplier analysis and CGE (computable general equilibrium) modeling. The context of the analysis is the immediate post-crisis period — most likely to be in the next millennium — represented in our study by a modified benchmark data set for 1995. Special attention is given to the overall income and equity effects, considering that egalitarian growth has become a particularly important development objective in Indonesia. The results of SAM multiplier analysis indicate relatively strong macro-linkages from agricultural demand-led (ADL) industrialization, yielding a significantly larger increase in real GDP compared to that arising from industrial development oriented to either food processing or light manufacturing. The simulation results based on CGE modeling, which take account of nonlinearities and supply constraints that are ignored in SAM analysis, bear out the dominant influence of demand linkages in showing that ADL industrialization is associated with a larger GDP increase than the two industrial-led development paths.Social accounting., Indonesia., Industrialization.,

On the "Medieval Climate Anomaly" and climate instability around the end of 9th century

In this study, reconstruction of MCA (Medieval Climate Anomaly) through proxy data was tried to clarify its nature. At first, "prayers for rain" records were collected from "Rikkokushi", six national histories of the ancient Japan, and the climate variation was clarified by their appearance changes. Next, the climate variation of Japan was compared with those from MCAreconstruction studies on many areas in the world. Furthermore, MCA was examined by comparison with its simulation by global circulation model. The main results are as follows: 1) There remain many records on prayers for rain from the end of the first millennium to the beginning of the second millennium, which may show that it was time of warm and dry climate condition. 2) During MCA, there might have been a period of cool and moist condition around 900, specifically from 880 to 910. 3) A prevailing circulation like La Nina on the Pacific Ocean played an important role in MCA. 4) Around the Atlantic Ocean, the North Atlantic Oscillation was usually at its positive mode, and played an important role for the climate there

Genus statistics using the Delaunay tessellation field estimation method: (I) tests with the Millennium Simulation and the SDSS DR7

We study the topology of cosmic large-scale structure through the genus statistics, using galaxy catalogues generated from the Millennium Simulation and observational data from the latest Sloan Digital Sky Survey Data Release (SDSS DR7). We introduce a new method for constructing galaxy density fields and for measuring the genus statistics of its isodensity surfaces. It is based on a Delaunay tessellation field estimation (DTFE) technique that allows the definition of a piece-wise continuous density field and the exact computation of the topology of its polygonal isodensity contours, without introducing any free numerical parameter. Besides this new approach, we also employ the traditional approaches of smoothing the galaxy distribution with a Gaussian of fixed width, or by adaptively smoothing with a kernel that encloses a constant number of neighboring galaxies. Our results show that the Delaunay-based method extracts the largest amount of topological information. Unlike the traditional approach for genus statistics, it is able to discriminate between the different theoretical galaxy catalogues analyzed here, both in real space and in redshift space, even though they are based on the same underlying simulation model. In particular, the DTFE approach detects with high confidence a discrepancy of one of the semi-analytic models studied here compared with the SDSS data, while the other models are found to be consistent.Comment: 14 pages, 9 figures, accepted by Ap

Structure in the 3D Galaxy Distribution: I. Methods and Example Results

Three methods for detecting and characterizing structure in point data, such as that generated by redshift surveys, are described: classification using self-organizing maps, segmentation using Bayesian blocks, and density estimation using adaptive kernels. The first two methods are new, and allow detection and characterization of structures of arbitrary shape and at a wide range of spatial scales. These methods should elucidate not only clusters, but also the more distributed, wide-ranging filaments and sheets, and further allow the possibility of detecting and characterizing an even broader class of shapes. The methods are demonstrated and compared in application to three data sets: a carefully selected volume-limited sample from the Sloan Digital Sky Survey redshift data, a similarly selected sample from the Millennium Simulation, and a set of points independently drawn from a uniform probability distribution -- a so-called Poisson distribution. We demonstrate a few of the many ways in which these methods elucidate large scale structure in the distribution of galaxies in the nearby Universe.Comment: Re-posted after referee corrections along with partially re-written introduction. 80 pages, 31 figures, ApJ in Press. For full sized figures please download from: http://astrophysics.arc.nasa.gov/~mway/lss1.pd

Hubble flow variations as a test for inhomogeneous cosmology

Context. Backreactions from large-scale inhomogeneities may provide an elegant explanation for the observed accelerated expansion of the universe without the need to introduce dark energy. Aims. We propose a cosmological test for a specific model of inhomogeneous cosmology, called timescape cosmology. Using large-scale galaxy surveys such as SDSS and 2MRS, we test the variation of expansion expected in the $\Lambda$-CDM model versus a more generic differential expansion using our own calibrations of bounds suggested by timescape cosmology. Method. Our test measures the systematic variations of the Hubble flow towards distant galaxies groups as a function of the matter distribution in the lines of sight to those galaxy groups. We compare the observed systematic variation of the Hubble flow to mock catalogues from the Millennium Simulation in the case of the $\Lambda$-CDM model, and a deformed version of the same simulation that exhibits more pronounced differential expansion. Results. We perform a series of statistical tests, ranging from linear regressions to Kolmogorov-Smirnov tests, on the obtained data. They consistently yield results preferring $\Lambda$-CDM cosmology over our approximated model of timescape cosmology. Conclusions. Our analysis of observational data shows no evidence that the variation of expansion differs from that of the standard $\Lambda$-CDM model.Comment: 20 pages, 21 figures, accepted for publication in A&

Assembly Bias and Splashback in Galaxy Clusters

We use publicly available data for the Millennium Simulation to explore the implications of the recent detection of assembly bias and splashback signatures in a large sample of galaxy clusters. These were identified in the SDSS/DR8 photometric data by the redMaPPer algorithm and split into high- and low-concentration subsamples based on the projected positions of cluster members. We use simplified versions of these procedures to build cluster samples of similar size from the simulation data. These match the observed samples quite well and show similar assembly bias and splashback signals. Previous theoretical work has found the logarithmic slope of halo density profiles to have a well-defined minimum whose depth decreases and whose radius increases with halo concentration. Projected profiles for the observed and simulated cluster samples show trends with concentration which are opposite to these predictions. In addition, for high-concentration clusters the minimum slope occurs at significantly smaller radius than predicted. We show that these discrepancies all reflect confusion between splashback features and features imposed on the profiles by the cluster identification and concentration estimation procedures. The strong apparent assembly bias is not reflected in the three-dimensional distribution of matter around clusters. Rather it is a consequence of the preferential contamination of low-concentration clusters by foreground or background groups.Comment: 17 pages, 16 figures, 3 tables, accepted versio