M. Ali Choudhary

Neural network models for inflation forecasting: an appraisal

We assess the power of diverse Artificial Neural-Network (ANN) models as forecasting tools for monthly inflation rates for 28 Organization for Economic Co-operation and Development (OECD) countries. In the context of short out-of-sample forecasting horizon we find that, on average, the ANN models were a superior predictor for inflation for 45% while the Autoregressive model of order one (AR1) model performed better for 23% of the countries. Furthermore, we develop arithmetic combinations of several ANN models and find that these may also serve as credible tools for forecasting inflation.

Is there really a gap between aggregate productivity and technology

The important contribution by Basu and Fernald (2002) shows that, in practice, there is a statistically significant gap between aggregate productivity and technology that can be attributed to inefficient product and labour markets. This is important, as it implies that the Solow residual is an imperfect index for aggregate technology change. We take a related approach and find that when we control for capacity utilization, time varying markup and account for externalities between industries, by employing a superior system estimator, the gap between the aggregate productivity and technology is shown to narrow considerably.

On smoothing macroeconomic time series using the modified HP filter

In business-cycle research, smoothing data is an essential first step to evaluate the extent to which model-generated moments stand up to their empirical counterparts. We put to test McDermott’s (1997) modified version of Hodrick and Prescott’s (1997) smoothing filter. On the one hand, our simulations suggest that relative to other filters, the modified HP-filter replicates better artificially generated series with known properties. On the other hand, using true data we find that autoregressive properties of smoothed series are not affected by the choice of smoothing HP filters, but the same does not hold when it comes to multivariate analysis. The later result is especially strong for annual data. We report results for a large set of countries.

Are Performance Conditions on Executive Options Driven by Fundamentals

A special feature of UK executive pay is the heavy reliance on performance conditions for executive share options. Using data compiled from 2002-2003 Remuneration Committee reports of 130 of Britains largest companies as well as linked data on analyst earnings forecasts and realised earnings, this paper computes probabilities of Britains CEOs meeting their performance conditions and how much this varies across firms. Our main findings are that there is not much cross-company variation in how tough performance conditions are, though there are some outliers. We also find that the probability of meeting the targets depends on certain fundamental variables such as the number of non-executive directors, salaries of the chairs of the remcom committees, CEO tenure, CEO base pay and CEO notice periods. While most of the variables have the some sign as expected from theory, the statistical relations are weak. Overall, our results provide some support that good corporate governance leads to tougher targets for CEOs but at the some time the weakness of these links suggests that there is still much room for improvement.

Finance and Inequality : The Distributional Impacts of Bank Credit Rationing

We analyze reductions in bank credit using a natural experiment where unprecedented flooding differentially affected banks that were more exposed to flooded regions in Pakistan. Using a unique dataset that covers the universe of consumer loans in Pakistan and this exogenous shock to bank funding, we find two key results. First, banks disproportionately reduce credit to new and less-educated borrowers, following an increase in their funding costs. Second, the credit reduction is not compensated by relatively more lending by less-affected banks. The empirical evidence suggests that adverse selection is the primary cause for banks disproportionately reducing credit to new borrowers.

The dominant borrower syndrome

ABSTRACT The financing channel of a fiscal stimulus matters for the size and the sign of the fiscal multiplier. We develop a general equilibrium model where a fiscal stimulus is partially bank-funded and the government becomes the dominant borrower from banks relative to entrepreneurs. This leads to a negative impact on credit spreads, investment and a contraction in output. We support our story with a structural vector autoregression for a sample of developing countries featuring the dominant borrower syndrome.

How Public Information Affects Asymmetrically Informed Lenders: Evidence from a Credit Registry Reform

We exploit exogenous variation in the amount of public information available to banks about a firm to empirically evaluate the importance of adverse selection in the credit market. A 2006 reform introduced by the State Bank of Pakistan (SBP) reduced the amount of public information available to Pakistani banks about a firms creditworthiness. Prior to 2006, the SBP published credit information not only about the firm in question but also (aggregate) credit information about the firms group (where the group was defined as the set of all firms that shared one or more director with the firm in question). After the reform, the SBP stopped providing the aggregate group-level information. We propose a model with differentially informed banks and adverse selection, which generates predictions on how this reform is expected to affect a banks willingness to lend. The model predicts that adverse selection leads less informed banks to reduce lending compared to more informed banks. We construct a measure for the amount of information each lender has about a firms group using the set of firm-bank lending pairs prior to the reform. We empirically show those banks with private information about a firm lent relatively more to that firm than other, less-informed banks following the reform. Remarkably, this reduction in lending by less informed banks is true even for banks that had a pre-existing relationship with the firm, suggesting that the strength of prior relationships does not eliminate the problem of imperfect information.

Sticky Prices in Customer Markets

This paper uses survey data on 884 firms from Iceland to test some of the implications of the theory of customer markets proposed by Phelps and Winter (1970). Responses indicate that customers are valuable to firms in accordance with the theory. Firms that list customers as the most valuable asset differ from others in more frequently responding that they would keep prices unchanged when interest rates change; they more frequently mention low prices or habit formation as a source of customer loyalty and they attract customers mainly through marketing and salesmanship. Price changes appear not to be an important policy for attracting and retaining customers.