Search Results
Working Paper
Commodity Exports, Financial Frictions and International Spillovers
This paper offers a solution to the international co-movement puzzle found in open-economy macroeconomic models. We develop a small open-economy (SOE) dynamic stochastic general equilibrium (DSGE) model describing three endogenous channels that capture spillovers from the world to a commodity exporter: a world commodity price channel, a domestic commodity supply channel and a financial channel. We estimate our model with Bayesian methods on two commodity-exporting SOEs, namely Canada and South Africa. In addition to explaining international business cycle synchronization, the new model ...
Discussion Paper
Drivers of Inflation: The New York Fed DSGE Model’s Perspective
After a sharp decline in the first few months of the COVID-19 pandemic, inflation rebounded in the second half of 2020 and surged through 2021. This post analyzes the drivers of these developments through the lens of the New York Fed DSGE model. Its main finding is that the recent rise in inflation is mostly accounted for by a large cost-push shock that occurred in the second quarter of 2021 and whose inflationary effects persist today. Based on the model’s reading of historical data, this shock is expected to fade gradually over the course of 2022, returning quarterly inflation to close to ...
Working Paper
Switching Volatility in a Nonlinear Open Economy
Uncertainty about an economy’s regime can change drastically around a crisis. An imported crisis such as the global financial crisis in the euro area highlights the effect of foreign shocks. Estimating an open-economy nonlinear dynamic stochastic general equilibrium model for the euro area and the United States including Markov-switching volatility shocks, we show that these shocks were significant during the global financial crisis compared with periods of calm. We describe how U.S. shocks from both the real economy and financial markets affected the euro area economy and how bond ...
Discussion Paper
Choosing the Right Policy in Real Time (Why That’s Not Easy)
As an economist, you make policy recommendations at any point in time that depend on what model of the economy you have in mind and on your assessment of the state of the economy. One can see these points play out in the current discussion about the timing of interest rate liftoff and the speed of the subsequent renormalization. If you think nominal rigidities are not all that important, you are likely to conclude that accommodative policies won’t do much for growth but will generate inflation. Similarly, if you are convinced that the economy is already firing on all cylinders, you may see ...
Report
Liquidity policies and systemic risk
The growth of wholesale-funded credit intermediation has motivated liquidity regulations. We analyze a dynamic stochastic general equilibrium model in which liquidity and capital regulations interact with the supply of risk-free assets. In the model, the endogenously time-varying tightness of liquidity and capital constraints generates intermediaries? leverage cycle, influencing the pricing of risk and the level of risk in the economy. Our analysis focuses on liquidity policies? implications for household welfare. Within the context of our model, liquidity requirements are preferable to ...
Working Paper
The U.S. Shale Oil Boom, the Oil Export Ban, and the Economy: A General Equilibrium Analysis Nida
This paper examines the e ects of the U.S. shale oil boom in a two-country DSGE model where countries produce crude oil, re ned oil products, and a non-oil good. The model in- {{p}} corporates di erent types of crude oil that are imperfect substitutes for each other as inputs into the re ning sector. The model is calibrated to match oil market and macroeconomic data for the U.S. and the rest of the world (ROW). {{p}} We investigate the implications of a signicant {{p}} increase in U.S. light crude oil production similar to the shale oil boom. Consistent with the data, our model predicts that ...
Working Paper
Computation of Policy Counterfactuals in Sequence Space
We propose an efficient procedure to solve for policy counterfactuals in linear models with occasionally binding constraints in sequence space. Forecasts of the variables relevant for the policy problem, and their impulse responses to anticipated policy shocks, constitute sufficient information to construct valid counterfactuals. Knowledge of the structural model equations or filtering of structural shocks is not required. We solve for deterministic and stochastic paths under instrument rules as well as under optimal policy with commitment or subgame-perfect discretion. As an application, we ...
Discussion Paper
The FRBNY DSGE Model Forecast
The U.S. economy has been in a gradual but slow recovery. Will the future be more of the same? This post presents the current forecasts from the Federal Reserve Bank of New York’s (FRBNY) DSGE model, described in our earlier “Bird’s Eye View” post, and discusses the driving forces behind the forecasts. Find the code used for estimating the model and producing all the charts in this blog series here. (We should reiterate that these are not the official New York Fed staff forecasts, but only an input to the overall forecasting process at the Bank.)
Discussion Paper
Combining Models for Forecasting and Policy Analysis
Model uncertainty is pervasive. Economists, bloggers, policymakers all have different views of how the world works and what economic policies would make it better. These views are, like it or not, models. Some people spell them out in their entirety, equations and all. Others refuse to use the word altogether, possibly out of fear of being falsified. No model is “right,” of course, but some models are worse than others, and we can have an idea of which is which by comparing their predictions with what actually happened. If you are open-minded, you may actually want to combine models in ...
Discussion Paper
The FRBNY DSGE Model Meets Julia
We have implemented the FRBNY DSGE model in a free and open-source language called Julia. The code is posted here on GitHub, a public repository hosting service. This effort is the result of a collaboration between New York Fed staff and folks from the QuantEcon project, whose aim is to coordinate development of high performance open-source code for quantitative economic modeling.