Is There More than One Way to be E-Stable?

We initially examine two different methods for learning about parameters in a Rational Expectations setting, and show that there are conflicting E-stability results. We show that this conflict also extends to Minimum State Variable (MSV) representations. One of these methods of learning lends itself to the examination of E-stability for the generic forward-looking rational expectations model. This leads to a completely general relationship between saddlepath stability and E-stability, and a generalization of MSV results.E-stability, Minimum state variable.

The magnitude of the macroeconomic impact of oil price: the case of BRICS

This paper aims to investigate the importance of the macroeconomic impact of oil prices variations on Brazil, Russia, India, China and South Africa (BRICS). The topic was selected due to the significance of those leading emerging economies in global markets and to the determining role of oil in the current economy of the BRICS. The research was built upon on the Granger causality test, the impulse response function and the Cholesky variance decomposition by fitting both linear and non-linear multivariate vector autoregression (VAR) models. The model includes oil price inflation and consumer price inflation, interest rates, unemployment rates, exchange rates, imports and exports, and total industrial production. The results showed a significant impact of oil prices on the BRICS economies mainly in terms of total industrial production, exports and imports, and evidence of asymmetry was found. The remaining outcomes showed different results depending on whether the country is oil-exporting or oil-importing

Fault-tolerant and finite-error localization for point emitters within the diffraction limit

We implement an estimator for determining the separation between two incoherent point sources. This estimator relies on image inversion interferometry and when used with the appropriate data analytics, it yields an estimate of the separation with finite-error, even when the sources come arbitrarily close together. The experimental results show that the technique has a good tolerance to noise and misalignment, making it an interesting consideration for high resolution instruments

Imperfection Information, Optimal Monetary Policy and Informational Consistency

This paper examines the implications of imperfect information (II) for optimal monetary policy with a consistent set of informational assumptions for the modeller and the private sector an assumption we term the informational consistency. We use an estimated simple NK model from Levine et al. (2012), where the assumption of symmetric II significantly improves the fit of the model to US data to assess the welfare costs of II under commitment, discretion and simple Taylor-type rules. Our main results are: first, common to all information sets we find significant welfare gains from commitment only with a zero-lower bound constraint on the interest rate. Second, optimized rules take the form of a price level rule, or something very close across all information cases. Third, the combination of limited information and a lack of commitment can be particularly serious for welfare. At the same time we find that II with lags introduces a ‘tying ones hands’ effect on the policymaker that may improve welfare under discretion. Finally, the impulse response functions under our most extreme imperfect information assumption (output and inflation observed with a two-quarter delay) exhibit hump-shaped behaviour and the fiscal multiplier is significantly enhanced in this case

Computation of LQ Approximations to Optimal Policy Problems in Different Information Settings under Zero Lower Bound Constraints

This paper describes a series of algorithms that are used to compute optimal policy under full and imperfect information. Firstly we describe how to obtain linear quadratic (LQ) approximations to a nonlinear optimal policy problem. We develop novel algorithms that are required as a result of having agents with forward-looking expectations, that go beyond the scope of those that are used when all equations are backward-looking; these are utilised to generate impulse response functions and second moments for the case of imperfect information. We describe algorithms for reducing a system to minimal form that are based on conventional approaches, and that are necessary to ensure that a solution for fully optimal policy can be computed. Finally we outline a computational algorithm that is used to generate solutions when there is a zero lower bound constraint for the nominal interest rate.

Saddlepath Learning

Saddlepath learning occurs when agents know the form but not the coefficients of the sad?dlepath relationship defining rational expectations equilibrium. Under saddlepath learning, we obtain a completely general relationship between determinacy and e-stability, and generalise Min?imum State Variable results previously derived only under full information. When the system is determinate, we show that a learning process based on the saddlepath is always e-stable. When the system is indeterminate, we find there is a unique MSV solution that is iteratively e-stable. However, in this case there is a sunspot solution that is learnable as well. We conclude by demon?strating that our results hold for any information set.e-stability, determinacy, learning, saddlepath stability.

Robust Monetary Rules under Unstructured and Structured Model Uncertainty

This paper compares two contrasting approaches to robust monetary policy design. The first developed by Hansen and Sargent (2003, 2007) assumes unstructured model uncertainty and uses a minimax robustness criterion to design monetary rules. This contrasts with an older literature that structures uncertainty by seeking rules that are robust across competing views of the economy. This paper carries out and compares robust design exercises using both approaches using a standard ‘canonical New Keynesian model’. We pay particular attention to a number of issues: First, we distinguish three possible forms of the implied game between malign nature and the policymaker in the Hansen-Sargent procedure. Second, in both approaches, we examine the consequences for robust rules of the zero lower bound (ZLB) constraint on the nominal interest rate, the monetary instrument. Finally, again for both types of robustness exercise we explore the implications of policy design when the policymaker is obliged to use simple Taylor-type interest rate rules.robustness, structured and unstructured uncertainty, zero lower bound interest rate constraint