The role of central bank operating procedures in an economy with productive government spending

The choice of either the rate of monetary growth or the nominal interest rate as the instrument controlled by monetary authorities has both positive and normative implications for economic performance. We reexamine some of the issues related to the choice of the monetary policy instrument in a dynamic general equilibrium model exhibiting endogenous growth in which a fraction of productive government spending is financed by means of issuing currency. When we evaluate the performance of the two monetary instruments attending to the fluctuations of endogenous variables, we find that the inflation rate is less volatile under nominal interest rate targeting. Concerning the fluctuations of consumption and of the growth rate, both monetary policy instruments lead to statistically equivalent volatilities. Finally, we show that none of these two targeting procedures displays unambiguously higher welfare levels.

Macroeconomic shocks and the business cycle: evidence from a structural factor model

We use a dynamic factor model to provide a semi-structural representation for 101 quarterly US macroeconomic series. We find that (i) the US economy is well described by a number of structural shocks between two and six. Focusing on the four-shock specification, we identify, using sign restrictions, two non-policy shocks, demand and supply, and two policy shocks, monetary and fiscal. We obtain the following results. (ii) Both supply and demand shocks are important sources of fluctuations; supply prevails for GDP, while demand prevails for employment and inflation. (ii) Policy matters, Both monetary and fiscal policy shocks have sizeable effects on output and prices, with little evidence of crowding out; both monetary and fiscal authorities implement important systematic countercyclical policies reacting to demand shocks. (iii) Negative demand shocks have a large long-run positive effect on productivity, consistently with the Schumpeterian "cleansing" view of recessions.

No news in business cycles

This paper uses a structural, large dimensional factor model to evaluate the role of 'news' shocks (shocks with a delayed effect on productivity) in generating the business cycle. We find that (i) existing small-scale VECM models are affected by 'non-fundamentalness' and therefore fail to recover the correct shock and impulse response functions; (ii) news shocks have a limited role in explaining the business cycle; (iii) their effects are in line with what predicted by standard neoclassical theory; (iv) the bulk of business cycle fluctuations are explained by shocks unrelated to technology.

Correcting Measurement Error Bias in Interaction Models with Small Samples

Several methods have been suggested to estimate non-linear models with interaction terms in the presence of measurement error. Structural equation models eliminate measurement error bias, but require large samples. Ordinary least squares regression on summated scales, regression on factor scores and partial least squares are appropriate for small samples but do not correct measurement error bias. Two stage least squares regression does correct measurement error bias but the results strongly depend on the instrumental variable choice. This article discusses the old disattenuated regression method as an alternative for correcting measurement error in small samples. The method is extended to the case of interaction terms and is illustrated on a model that examines the interaction effect of innovation and style of use of budgets on business performance. Alternative reliability estimates that can be used to disattenuate the estimates are discussed. A comparison is made with the alternative methods. Methods that do not correct for measurement error bias perform very similarly and considerably worse than disattenuated regression

Two-sided learning in new keynesian models: dynamics, (lack of) convergence and the value of information

This paper investigates the role of learning by private agents and the central bank (two-sided learning) in a New Keynesian framework in which both sides of the economy have asymmetric and imperfect knowledge about the true data generating process. We assume that all agents employ the data that they observe (which may be distinct for different sets of agents) to form beliefs about unknown aspects of the true model of the economy, use their beliefs to decide on actions, and revise these beliefs through a statistical learning algorithm as new information becomes available. We study the short-run dynamics of our model and derive its policy recommendations, particularly with respect to central bank communications. We demonstrate that two-sided learning can generate substantial increases in volatility and persistence, and alter the behavior of the variables in the model in a signifficant way. Our simulations do not converge to a symmetric rational expectations equilibrium and we highlight one source that invalidates the convergence results of Marcet and Sargent (1989). Finally, we identify a novel aspect of central bank communication in models of learning: communication can be harmful if the central bank's model is substantially mis-specified

Adaptive business intelligence for an open negotiation environment

Engineering of negotiation model allows to develop effective heuristic for business intelligence. Digital ecosystems demand open negotiation models. To define in advance effective heuristics is not compliant with the requirement of openness. The new challenge is to develop business intelligence in advance exploiting an adaptive approach. The idea is to learn business strategy once new negotiation model rise in the e-market arena. In this paper we present how recommendation technology may be deployed in an open negotiation environment where the interaction protocol models are not known in advance. The solution we propose is delivered as part of the ONE Platform, open source software that implements a fully distributed open environment for business negotiation

How does ownership structure invfluence bank risk? Analyzing the role of managerial incentives

This paper analyzes how ownership concentration and managerial incentives influences bank risk for a large sample of US banks over the period 1997-2007. Using 2SLS simultaneous equations models, we show that ownership concentration has a positive total effect on bank risk. This is the result of a positive direct effect, which reflects monitoring and opportunistic behavior, and a negative indirect effect, which works through the design of managerial incentive contracts and reflects shareholder preferences toward risk. Large shareholders reduce bank risk by reducing the sensitivity of CEO wealth to stock volatility (Vega) and by increasing the CEO pay-performance sensitivity (Delta). In addition, we show that the direct and indirect effect of ownership concentration on bank risk depends on the type of the largest shareholder (a family, a bank, a corporation or an institutional investor), as well as, on the total shareholding held by each type as a group. Our results suggest that the positive relation between ownership concentration and risk is not the result of preferences towards more risk. Rather, they point at opportunistic behavior of large shareholders.

How Doing Business Jeopardizes Institutional Reform

Simplifying business formalization and eliminating outdated formalities is often a good way of improving the institutional environment for firms. Unfortunately, the World Bank's Doing Business project is harming such policies by promoting a reform agenda that gives them priority even in countries lacking functional business registers, so that the reformed registers keep producing valueless information, but faster. Its methodology also promotes biased measurements that impede proper consideration of the essential tradeoffs in the design of formalization institutions. If Doing Business is to stop jeopardizing its true objectives and contribute positively to scientific progress, institutional reform and economic development, then its aims, governance and methodology need to change.

Open source business strategies in the domain of embedded systems

El tema de este estudio es el aumento de la comprensión teórica y empírica de la estrategia de negocio de código abierto en el dominio de sistemas embebidos por investigar modelos de negocios de código abierto, retos, recursos y capacidades operativas y dinámicas.

International business cycles, financial markets and household production

This paper investigates the properties of an international real business cycle model with household production. We show that a model with disturbances to both market and household technologies reproduces the main regularities of the data and improves existing models in matching international consumption, investment and output correlations without irrealistic assumptions on the structure of international financial markets. Sensitivity analysis shows the robustness of the results to alternative specifications of the stochastic processes for the disturbances and to variations of unmeasured parameters within a reasonable range.

What do outside experts bring to a committee? Evidence from the Bank of England

We test whether outside experts have information not available to insiders by usingthe voting record of the Bank of England's Monetary Policy Committee. Memberswith more private information should vote more often against conventional wisdom,which we measure as the average belief of market economists about future interest rates. We find evidence that external members indeed have information notavailable to internals, but also use a quasi-natural experiment to show they mayexaggerate their expertise to obtain reappointment. This implies that an optimalcommittee, even outside monetary policy, should potentially include outsiders, butneeds to manage career concerns.

Two-sided learning in New Keynesian models: Dynamics, (lack of) convergence and the value of information

This paper investigates the role of learning by private agents and the central bank(two-sided learning) in a New Keynesian framework in which both sides of the economyhave asymmetric and imperfect knowledge about the true data generating process. Weassume that all agents employ the data that they observe (which may be distinct fordifferent sets of agents) to form beliefs about unknown aspects of the true model ofthe economy, use their beliefs to decide on actions, and revise these beliefs througha statistical learning algorithm as new information becomes available. We study theshort-run dynamics of our model and derive its policy recommendations, particularlywith respect to central bank communications. We demonstrate that two-sided learningcan generate substantial increases in volatility and persistence, and alter the behaviorof the variables in the model in a significant way. Our simulations do not convergeto a symmetric rational expectations equilibrium and we highlight one source thatinvalidates the convergence results of Marcet and Sargent (1989). Finally, we identifya novel aspect of central bank communication in models of learning: communicationcan be harmful if the central bank's model is substantially mis-specified.

Bridging DSGE models and the raw data

A method to estimate DSGE models using the raw data is proposed. The approachlinks the observables to the model counterparts via a flexible specification which doesnot require the model-based component to be solely located at business cycle frequencies,allows the non model-based component to take various time series patterns, andpermits model misspecification. Applying standard data transformations induce biasesin structural estimates and distortions in the policy conclusions. The proposed approachrecovers important model-based features in selected experimental designs. Twowidely discussed issues are used to illustrate its practical use.

Business cycle measurement with some theory

A method to evaluate cyclical models not requiring knowledge of the DGP and the exact specificationof the aggregate decision rules is proposed. We derive robust restrictions in a class of models; use someto identify structural shocks in the data and others to evaluate the class or contrast sub-models. Theapproach has good properties, even in small samples, and when the class of models is misspecified. Themethod is used to sort out the relevance of a certain friction (the presence of rule-of-thumb consumers)in a standard class of models.

Credit rationing and crowding out during the Industrial Revolution: Evidence from Hoare's Bank, 1702-1862

Crowding-out during the British Industrial Revolution has long been one of the leadingexplanations for slow growth during the Industrial Revolution, but little empirical evidence exists to support it. We argue that examinations of interest rates are fundamentally misguided, and that the eighteenth- and early nineteenth-century private loan market balanced through quantity rationing. Using a unique set of observations on lending volume at a London goldsmith bank, Hoare s, we document the impact of wartime financing on private credit markets. We conclude that there is considerable evidence that government borrowing, especially during wartime, crowded out private credit.