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Compositional Data Analysis in Practice is a user-oriented practical guide to the analysis of data with the property of a constant sum, for example percentages adding up to 100%. Compositional data can give misleading results if regular statistical methods are applied, and are best analysed by first transforming them to logarithms of ratios. This book explains how this transformation affects the analysis, results and interpretation of this very special type of data. All aspects of compositional data analysis are considered: visualization, modelling, dimension-reduction, clustering and variable selection, with many examples in the fields of food science, archaeology, sociology and biochemistry, and a final chapter containing a complete case study using fatty acid compositions in ecology. The applicability of these methods extends to other fields such as linguistics, geochemistry, marketing, economics and finance.R SoftwareThe R package easyCODA, which accompanies this book, can be downloaded from R-Forge as follows: install.packages and will be available on CRAN soon. Notice that the R packages ca and vegan also have to be installed (from CRAN in the usual way)

Quantitative research. --- Principal components analysis. --- Electronic data processing.

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We build a factor-augmented interacted panel vector-autoregressive model of the Euro Area (EA) and estimate it with Bayesian methods to compute government spending multipliers. The multipliers are contingent on the overall monetary policy stance, captured by a shadow monetary policy rate. In the short run (one year), whether the fiscal shock occurs when the economy is at the effective lower bound (ELB) or in normal times does not seem to matter for the size of the multiplier. However, as the time horizon increases, multipliers diverge across the two regimes. In the medium run (three years), the average multiplier is about 1 in normal times and between 1.6 and 2.8 at the ELB, depending on the specification. The difference between the two multipliers is distributed largely away from zero. More generally, the multiplier is inversely correlated with the level of the shadow monetary policy rate. In addition, we verify that EA data lend support to the view that the multiplier is larger in periods of economic slack, and we show that the shadow rate and the state of the business cycle are autonomously correlated with its size. The econometric approach deals with several technical problems highlighted in the empirical macroeconomic literature, including the issues of fiscal foresight and limited information.

Banks and Banking --- Macroeconomics --- Money and Monetary Policy --- Public Finance --- Time-Series Models --- Dynamic Quantile Regressions --- Dynamic Treatment Effect Models --- Diffusion Processes --- State Space Models --- Multiple or Simultaneous Equation Models: Models with Panel Data --- Classification Methods --- Cluster Analysis --- Principal Components --- Factor Models --- Fiscal Policy --- National Government Expenditures and Related Policies: General --- Interest Rates: Determination, Term Structure, and Effects --- Prices, Business Fluctuations, and Cycles: General (includes Measurement and Data) --- Public finance & taxation --- Monetary economics --- Economic growth --- Banking --- Expenditure --- Interest rate floor --- Business cycles --- Central bank policy rate --- Fiscal multipliers --- Monetary policy --- Financial services --- Fiscal policy --- Expenditures, Public --- Interest rates --- United States

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This paper studies changes in the transmission of common versus sectoral idiosyncratic shocks across different U.S. nonfarm business sectors during the Great Recession, and evaluates the cross-sectoral spillovers. Shocks are identified by dynamic factor methods. We find that the Great Recession is largely a time of heightened impact of common shocks— which accounts for 3/4 of aggregate volatility—and large spillovers of negative financerelated shocks. Moreover, in contrast with the earlier literature that failed to find a significant role of sectoral shocks (propagated through the input-output linkages across sectors) in driving variability in aggregate industry output, this study allows spillovers of shocks to operate through other mechanisms intertemporally. We find that prior to the recession the majority of aggregate fluctuations is explained by sector-specific shocks.

Recessions. --- Financial crises. --- Crashes, Financial --- Crises, Financial --- Financial crashes --- Financial panics --- Panics (Finance) --- Stock exchange crashes --- Stock market panics --- Crises --- Business cycles --- Depressions --- Econometrics --- Macroeconomics --- Industries: Manufacturing --- Time-Series Models --- Dynamic Quantile Regressions --- Dynamic Treatment Effect Models --- Diffusion Processes --- State Space Models --- Input-Output Models --- Business Fluctuations --- Cycles --- Macroeconomics: Production --- Classification Methods --- Cluster Analysis --- Principal Components --- Factor Models --- Industry Studies: Manufacturing: General --- Financial Crises --- Econometrics & economic statistics --- Manufacturing industries --- Economic & financial crises & disasters --- Production growth --- Vector autoregression --- Factor models --- Manufacturing --- Structural vector autoregression --- Global financial crisis of 2008-2009 --- Financial crises --- Production --- Econometric analysis --- Economic sectors --- Economic theory --- Econometric models --- Global Financial Crisis, 2008-2009 --- United States

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This paper investigates the developments in house price synchronization across countries by a dynamic factor model using a country- and city-level dataset, and examines what drives the synchronization. The empirical results indicate that: (i) the degree of synchronization has been rising since the 1970s, and (ii) a large heterogeneity in the degree of synchronization exists across countries and cities. A panel and cross-sectional regression analysis show that the heterogeneity of synchronization is partly accounted for by the progress in financial and trade openness. Also, the city-level analysis implies that the international synchronization is mainly driven by the city-level connectivity between large and international cities.

Macroeconomics --- Economics: General --- International Economics --- Real Estate --- Econometrics --- Infrastructure --- Inflation --- Foreign Exchange --- Informal Economy --- Underground Econom --- Classification Methods --- Cluster Analysis --- Principal Components --- Factor Models --- Financial Aspects of Economic Integration --- International Financial Markets --- Housing Supply and Markets --- Economic Development: Urban, Rural, Regional, and Transportation Analysis --- Housing --- Price Level --- Deflation --- Economic & financial crises & disasters --- Economics of specific sectors --- Property & real estate --- Econometrics & economic statistics --- Financial crises --- Economic sectors --- Housing prices --- Prices --- Factor models --- Econometric analysis --- National accounts --- Currency crises --- Informal sector --- Economics --- Econometric models --- Saving and investment --- China, People's Republic of