Nikita Perevalov


The Complex Adjustment of the Canadian Economy to Lower Commodity Prices

In this analytical note, we provide a comprehensive assessment of the complex structural adjustment facing the Canadian economy following the commodity price decline since mid-2014. We quantify separately the impacts coming from the commodity sector restructuring and the broader effect of significantly lower terms of trade.

Countercyclical Bank Capital Requirement and Optimized Monetary Policy Rules

Using BoC-GEM-Fin, a large-scale DSGE model with real, nominal and financial frictions featuring a banking sector, we explore the macroeconomic implications of various types of countercyclical bank capital regulations. Results suggest that countercyclical capital requirements have a significant stabilizing effect on key macroeconomic variables, but mostly after financial shocks.
May 17, 2012

On the Adjustment of the Global Economy

This article discusses three scenarios for the adjustment of the global economy. In a “baseline” scenario—which encompasses fiscal consolidation in major advanced economies, growth-friendly structural reforms in Europe and Japan, and greater exchange rate flexibility and reforms in the emerging-market economies of Asia to induce rotation of demand away from net exports—global current account imbalances […]

The Macroeconomic Implications of Changes in Bank Capital and Liquidity Requirements in Canada: Insights from the BoC-GEM-FIN

Staff Discussion Paper 2010-16 Carlos De Resende, Ali Dib, Nikita Perevalov
The authors use simulations within the BoC-GEM-FIN, the Bank of Canada's version of the Global Economy Model with financial frictions in both the demand and supply sides of the credit market, to investigate the macroeconomic implications of changing bank regulations on the Canadian economy.

On the Advantages of Disaggregated Data: Insights from Forecasting the U.S. Economy in a Data-Rich Environment

Staff Working Paper 2010-10 Nikita Perevalov, Philipp Maier
The good forecasting performance of factor models has been well documented in the literature. While many studies focus on a very limited set of variables (typically GDP and inflation), this study evaluates forecasting performance at disaggregated levels to examine the source of the improved forecasting accuracy, relative to a simple autoregressive model. We use the latest revision of over 100 U.S. time series over the period 1974-2009 (monthly and quarterly data).

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