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This paper analyzes and reconciles macro and micro evidence on savings and factors that affect savings, as well as possible policy implications. At the aggregate level, the main question is how savings are affected by growth and macroeconomic policies and variables (fiscal policy, exchange rate, for example) and the breadth of financial markets. Some of these macro determinants can be reconciled with microeconomic evidence of the savings behavior of households. Using macroeconomic quarterly data and household survey data, the analysis explores the determinants of the savings rate at the macroeconomic and microeconomic levels, using the typical econometric models used in the literature (long-term co-integration relation and short-term error correction model for the macro determinants; linear multivariate models for the micro determinants). The long-term relationship indicates that a 10-percent increase in gross domestic product per capita would add 3.7 percentage points to the savings rate in the long run. The short-term relationship depicts a strong catch-up process to the long-run equilibrium, with quarterly changes in gross domestic product per capita and openness strongly correlated with quarterly changes in the savings rate. The characteristics of households that represent the volatility of expected income, such as education and access to borrowing or remittances, significantly impact saving rates. The macroeconomic and microeconomic analyses of the determinants of saving rates in Armenia point to three policy areas: the macroeconomic environment, the financial sector, and the role of remittances.
Access to Finance --- Debt Markets --- Economic Theory & Research --- Emerging Markets --- Error Correction Model --- Growth --- Macroeconomics and Economic Growth --- Poverty Reduction --- Remittances --- Rural Poverty Reduction --- Saving
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53.088 --- 53.088 Errors. Error correction. Evaluation, interpretation of measurements --- Errors. Error correction. Evaluation, interpretation of measurements --- Error analysis (Mathematics) --- Physical measurements --- Measurements, Physical --- Mathematical physics --- Measurement --- Errors, Theory of --- Instrumental variables (Statistics) --- Mathematical statistics --- Numerical analysis --- Statistics --- Measuring methods in physics --- Error analysis (Mathematics). --- Physical measurements. --- Erreurs, Théorie des --- Mesures physiques
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Measuring methods in physics --- Mathematical physics --- Physical measurements. --- Error analysis (Mathematics) --- Mathematical physics. --- Mesures physiques --- Erreurs, Théorie des --- Physique mathématique --- Physics --- Mesure --- Measurement --- 53.088 --- Physical measurements --- #WSCH:AAS1 --- Measurements, Physical --- Physical mathematics --- Errors, Theory of --- Instrumental variables (Statistics) --- Mathematical statistics --- Numerical analysis --- Statistics --- Errors. Error correction. Evaluation, interpretation of measurements --- Mathematics --- Error analysis (Mathematics). --- 53.088 Errors. Error correction. Evaluation, interpretation of measurements --- Erreurs, Théorie des --- Physique mathématique --- MATHEMATICAL PHYSICS --- MATHEMATICS --- ERROR ANALYSIS --- Monograph --- Mathematics. --- Math --- Science --- Statistique mathématique --- Mathematical statistics. --- Statistique mathématique --- Physique statistique --- Calcul d'erreur --- Theorie des erreurs
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This paper studies asymptotically the bias of the fixed effect (FE) estimator induced by cross-section heterogeneity in the slope parameters of stationary vector autoregressions (VARs). The paper also compares the FE, the mean group estimator (MG), and a simple instrumental variable alternative (IV) in Monte Carlo simulations. The main results are: (i) asymptotically, the heterogeneity bias of the FE may be more or less severe in VAR specifications than in standard dynamic panel data specifications; (ii) in Monte Carlo simulations, slope heterogeneity must be relatively high to be a source of concern for pooled estimators; (iii) when this happens, the panel must be longer than a typical macro dataset for the MG to be a viable solution.
Econometrics --- Multiple or Simultaneous Equation Models: Models with Panel Data --- Estimation --- Simulation Methods --- Time-Series Models --- Dynamic Quantile Regressions --- Dynamic Treatment Effect Models --- Diffusion Processes --- Multiple or Simultaneous Equation Models --- Multiple Variables: General --- Econometrics & economic statistics --- Vector autoregression --- Vector error correction models --- Econometric models
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The paper estimates a behavioral equilibrium exchange rate model for Ghana. Regression results show that most of the REER's long-run behavior can be explained by real GDP growth, real interest rate differentials (both relative to trading-partner countries), and the real world prices of Ghana's main export commodities. On the basis of these fundamentals, the REER in late 2006 was found to be very close to its estimated equilibrium level. The results also suggest, that deviations from the equilibrium path are eliminated within two to three years.
Banks and Banking --- Econometrics --- Exports and Imports --- Foreign Exchange --- Interest Rates: Determination, Term Structure, and Effects --- Multiple or Simultaneous Equation Models --- Multiple Variables: General --- Trade: General --- Currency --- Foreign exchange --- Finance --- Econometrics & economic statistics --- International economics --- Real effective exchange rates --- Real exchange rates --- Real interest rates --- Vector error correction models --- Exports --- Interest rates --- Econometric models --- Ghana --- Competition --- Foreign exchange rates --- Economic policy.
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We investigate the properties of Johansen's (1988, 1991) maximum eigenvalue and trace tests for cointegration under the empirically relevant situation of near-integrated variables. Using Monte Carlo techniques, we show that in a system with near-integrated variables, the probability of reaching an erroneous conclusion regarding the cointegrating rank of the system is generally substantially higher than the nominal size. The risk of concluding that completely unrelated series are cointegrated is therefore non-negligible. The spurious rejection rate can be reduced by performing additional tests of restrictions on the cointegrating vector(s), although it is still substantially larger than the nominal size.
Econometrics --- Foreign Exchange --- Inflation --- Price Level --- Deflation --- Time-Series Models --- Dynamic Quantile Regressions --- Dynamic Treatment Effect Models --- Diffusion Processes --- Multiple or Simultaneous Equation Models --- Multiple Variables: General --- Currency --- Foreign exchange --- Econometrics & economic statistics --- Macroeconomics --- Real exchange rates --- Vector autoregression --- Vector error correction models --- Prices --- Econometric models --- United States --- Econometric models. --- Autoregression (Statistics)
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Several authors have recently investigated the predictability of exchange rates by fitting a sequence of long-horizon error-correction regressions. By considering the implied vector error-correction model, we show that little is to be gained from estimating such regressions for horizons greater than one time period. We also show that in small to medium samples the long-horizon procedure gives rise to spurious evidence of predictive power. A simulation study demonstrates that even when using this technique on two independent series, estimates, diagnostic statistics and graphical evidence incorrectly suggest a high degree of predictability of the dependent variable.
Econometrics --- Foreign Exchange --- Time-Series Models --- Dynamic Quantile Regressions --- Dynamic Treatment Effect Models --- Diffusion Processes --- State Space Models --- Simulation Methods --- Multiple or Simultaneous Equation Models --- Multiple Variables: General --- Currency --- Foreign exchange --- Econometrics & economic statistics --- Exchange rates --- Vector error correction models --- Econometric analysis --- Econometric models --- United States
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This paper develops a time series model for aggregate consumption to predict the U.S. personal saving rate. It then uses the model to test whether there has been a structural break in consumption behavior because of the 2008 financial crisis. Before the crisis, the personal saving rate was trending downwards. However, in 2008 there was a significant rise in the saving rate that continued until the end of 2012, suggesting a permanent change in household behavior. To assess this issue formally, the unknown parameters of the model are estimated using data for 1961Q1-2007Q4, a period which precedes the crisis. The model is then used to predict the saving rate from 2008Q1 onwards and to assess whether the rise in the saving rate after 2008 was due to sizable, but transitory, income/wealth shocks or to changes in the underlying elasticities between saving and its determinants (hence structural). The statistical evidence suggests there was no structural break in the household saving behavior, implying that the rise in the saving rate during 2008-2012 was caused by the negative shocks to income, employment and wealth. This result explains why the saving rate resumed its decline in 2013, as real disposable income, employment and net worth recovered. Assuming that the real growth in these determinants remains strong, the estimated model predicts continued negative pressures on the current account deficit and further external imbalances attributable to the U.S. household sector.
Econometrics --- Macroeconomics --- Consumer Economics: Empirical Analysis --- Personal Finance --- Macroeconomics: Consumption --- Saving --- Wealth --- Forecasting and Simulation: Models and Applications --- Personal Income, Wealth, and Their Distributions --- Multiple or Simultaneous Equation Models --- Multiple Variables: General --- Aggregate Factor Income Distribution --- Econometrics & economic statistics --- Consumption --- Disposable income --- Private savings --- Vector error correction models --- Income --- National accounts --- Econometric analysis --- Economics --- National income --- Saving and investment --- Econometric models --- United States
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Would better state institutions increase tax collection, or would higher tax collection help improve state institutions? In the absence of conclusive guidance from theory, this paper searches for an empirical answer to this question, using a panel dataset covering 110 non-resource-rich countries from 1996 to 2017. Employing a panel vector error correction model, the paper finds that tax capacity and state institutions cause and reinforce each other for a wide range of country groups. The bi-directional causality results suggest that developing tax capacity and building state institutions need to go hand in hand for best results, particularly in developing countries. Based on the impulse response analyses, the paper also finds that the causal effects in advanced economies are generally low in both directions, while in developing countries, both tax capacity and institutions shocks have larger positive impacts on institutions and tax capacity, respectively.
Econometrics --- Public Finance --- Taxation --- Structure, Scope, and Performance of Government --- Tax Evasion and Avoidance --- 'Panel Data Models --- Spatio-temporal Models' --- Taxation, Subsidies, and Revenue: General --- Multiple or Simultaneous Equation Models --- Multiple Variables: General --- Public finance & taxation --- Econometrics & economic statistics --- Revenue administration --- Vector error correction models --- Subnational tax --- Revenue Administration Fiscal Information Tool (RA-FIT) --- Revenue --- Econometric models --- Panel Data Models --- Spatio-temporal Models
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