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Many emerging-market economies (EMEs) have significantly improved their macroeconomic fundamentals and undergone structural reforms since the Asian crisis. These developments have enhanced the composition of capital flows to EMEs through an improved debt structure, a larger share of capital flows as foreign direct investment, and greater access to international debt markets for corporations in EMEs. Structural changes in the global financial landscape have also increased capital flows, bringing economic and financial benefits to EMEs. During the recent financial crisis, however, the opening up of capital accounts and increased financial and trade linkages left many countries vulnerable to external disruptions. Countries with sound fundamentals have weathered the crisis relatively well. Policy-makers in EMEs need to implement policies that support capital flows and ensure that controls imposed to deal with detrimental outflows during periods of stress or rapid inflows are only temporary.

Using data from patents, citations, inter-sectoral sales and customs, we examine the international diffusion of technology through imports of sectoral knowledge and production inputs. We develop an instrumental variable strategy to identify the causal effects of technology embodied in imports on innovation and diffusion outcomes.

We explore what drives transaction fees in the Bitcoin system and consider whether Bitcoin can remain tamper proof in the long run.

Using turnover ratios, Anderson and Lavoie describe the recent evolution of liquidity in various secondary government bond markets, focusing specifically on the market for Government of Canada securities. They attribute much of the recent variation in liquidity to such cyclical factors as changes in the interest rate environment and investors' appetite for risk, as well as developments in equity markets in the late 1990s. They also examine longer-term structural and policy-related trends, including the rate of adoption of financial and technological innovations and the level of government borrowing and debt-management initiatives.

While the Bank of Canada's inflation-control target is specified in terms of the rate of increase in the total consumer price index, the Bank uses a measure of trend or "core" inflation as a short-term guide for its monetary policy actions. When the inflation targets were renewed in May 2001, the Bank announced that it was adopting a new measure of core inflation. This measure excludes the eight most volatile components of the CPI and adjusts the remaining components for the effect of changes in indirect taxes. In this article, the author discusses the definition of the new measure of core inflation and describes some of its advantages relative to the previous measure. He notes that the new measure has a firmer statistical basis, has a better correspondence with economic theory, and does a better job of predicting future changes in overall inflation. While the new measure has these advantages, the Bank will continue to monitor a broad range of indicators when assessing the likely future path for inflation.

This paper studies the effects of monetary policy shocks on firms’ participation in exporting. We develop a two-country dynamic stochastic general equilibrium model in which heterogeneous firms make forward-looking decisions on whether to participate in the export market and prices are staggered across firms and time.

How wrong could policymakers be when using linearized solutions to their macroeconomic models instead of nonlinear global solutions?

A low level of the neutral rate of interest increases the likelihood that a central bank’s policy rate will reach its effective lower bound (ELB) in future economic downturns. In a low neutral rate environment, using an extended monetary policy toolkit including forward guidance helps address the ELB challenge. Using the Bank’s Terms-of-Trade Economic Model, we assess the benefits and limitations of a state-contingent forward guidance implemented within a flexible inflation targeting framework.

Worst-case analysis is used among financial regulators in the wake of the recent financial crisis to gauge the tail risk. We provide insight into worst-case analysis and provide guidance on how to estimate it. We derive the bias for the non-parametric heavy-tailed order statistics and contrast it with the semi-parametric extreme value theory (EVT) approach.

I develop a population-based Markov chain Monte Carlo algorithm known as parallel tempering to estimate dynamic stochastic general equilibrium models. Parallel tempering approximates the posterior distribution of interest using a family of Markov chains with tempered posteriors.