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We leverage insights from machine learning to optimize the tradeoff between bias and variance when estimating economic models using pooled datasets. Specifically, we develop a simple algorithm that estimates the similarity of economic structures across countries and selects the optimal pool of countries to maximize out-of-sample prediction accuracy of a model. We apply the new alogrithm by nowcasting output growth with a panel of 102 countries and are able to significantly improve forecast accuracy relative to alternative pools. The algortihm improves nowcast performance for advanced economies, as well as emerging market and developing economies, suggesting that machine learning techniques using pooled data could be an important macro tool for many countries.

Macroeconomics --- Intelligence (AI) & Semantics --- Forecasting and Other Model Applications --- Neural Networks and Related Topics --- Technological Change: Choices and Consequences --- Diffusion Processes --- Macroeconomics: Production --- Machine learning --- Production growth --- Technology --- Production --- Economic theory --- Costa Rica

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We leverage insights from machine learning to optimize the tradeoff between bias and variance when estimating economic models using pooled datasets. Specifically, we develop a simple algorithm that estimates the similarity of economic structures across countries and selects the optimal pool of countries to maximize out-of-sample prediction accuracy of a model. We apply the new alogrithm by nowcasting output growth with a panel of 102 countries and are able to significantly improve forecast accuracy relative to alternative pools. The algortihm improves nowcast performance for advanced economies, as well as emerging market and developing economies, suggesting that machine learning techniques using pooled data could be an important macro tool for many countries.

Costa Rica --- Macroeconomics --- Intelligence (AI) & Semantics --- Forecasting and Other Model Applications --- Neural Networks and Related Topics --- Technological Change: Choices and Consequences --- Diffusion Processes --- Macroeconomics: Production --- Machine learning --- Production growth --- Technology --- Production --- Economic theory

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We study the process of external adjustment to large terms-of-trade level shifts—identified with a Markov-switching approach—for a large set of countries during the period 1960–2015. We find that adjustment to these shocks is relatively fast. Current accounts experience, on average, a contemporaneous variation of only about ½ of the magnitude of the price shock—indicating a significant volume offset—and a full adjustment within 3–4 years. Dynamics are largely symmetric for terms-of-trade booms and busts, as well as for advanced and emerging market economies. External adjustment is driven primarily by offsetting shifts in domestic demand, as opposed to variations in output (also reflected in the response of import rather than export volumes), indicating a strong income channel at play. Exchange rate flexibility appears to have played an important buffering role during booms, but less so during busts; while international reserve holdings have been a key tool for smoothing the adjustment process.

Business cycles --- Business cycles. --- Economic cycles --- Economic fluctuations --- Cycles --- Econometric models. --- Exports and Imports --- Foreign Exchange --- Information Management --- Current Account Adjustment --- Short-term Capital Movements --- Open Economy Macroeconomics --- International Business Cycles --- Technological Change: Choices and Consequences --- Diffusion Processes --- Knowledge management --- International economics --- Currency --- Foreign exchange --- Technology transfer --- Current account --- Exchange rate arrangements --- Adjustment process --- Exchange rate flexibility --- Technology --- Balance of payments --- United States

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Automated trade execution systems are examined with respect to the degree to which they automate the price discovery process. Seven levels of automation of price discovery are identified, and 47 systems are classified according to these criteria. Systems operating at various levels of automation are compared with respect to age, geographical location, and type of securities traded. Information provided to market participants, and asymmetries of information between traders with direct access to the automated market and outside investors also are examined. It is found, for example, that the degree of asymmetric information increases with the level of automation of price discovery. The potential for trading abuses related to prearranged trading, noncompetitive execution, and trading ahead of customers is analyzed for each level of automation. Certain levels of automation widen the opportunities for trading abuses in some respects, but may narrow them in others.

Automatic control engineering --- Automation --- Derivative securities --- Diffusion Processes --- Exports and Imports --- Finance --- Financial institutions --- Financial Instruments --- Futures --- Institutional Investors --- International economics --- International Trade Organizations --- International trade --- Investment & securities --- Investments: Futures --- Investments: Options --- Investments: Stocks --- Non-bank Financial Institutions --- Options --- Pension Funds --- Stocks --- Technological Change: Choices and Consequences --- Technology --- Trade Policy --- Trade systems --- United States

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This work presents a new technique for temporally benchmarking a time series according to the growth rates preservation principle (GRP) by Causey and Trager (1981). A procedure is developed which (i) transforms the original constrained problem into an unconstrained one, and (ii) applies a Newton's method exploiting the analytic Hessian of the GRP objective function. We show that the proposed technique is easy to implement, computationally robust and efficient, all features which make it a plausible competitor of other benchmarking procedures (Denton, 1971; Dagum and Cholette, 2006) also in a data-production process involving a considerable amount of series.

Time-series analysis. --- Analysis of time series --- Autocorrelation (Statistics) --- Harmonic analysis --- Mathematical statistics --- Probabilities --- Intelligence (AI) & Semantics --- Time-Series Models --- Dynamic Quantile Regressions --- Dynamic Treatment Effect Models --- Diffusion Processes --- Optimization Techniques --- Programming Models --- Dynamic Analysis --- Methodology for Collecting, Estimating, and Organizing Macroeconomic Data --- Data Access --- Technological Change: Choices and Consequences --- Artificial intelligence --- Technology --- United States