General-to-specific modelling technique

In Hendry’s approach, econometric models are formulated based on statistical data and economic theory. Statistical data are realizations from the DGP whereas economic theory guides the econometric specification. As Hendry (1983) argues, every empirical model is a reduction of the underlying DGP, and it is nested in the DGP. In sum, Hendry’s approach is a simplification of the unknown DGP.

Pagan (1987) summarizes Hendry’s methodology as the following four steps. The first step formulates an initial general model, based on economic theory, to suggest which variables might enter the equilibrium specification. Such a general unrestricted model provides an approximation of the DGP. At this stage, the lag length for each variable is chosen to be as large as econometrically feasible. The next step involves reparameterizing the model into an error-correction representation so that it is easier to understand and interpret in terms of the final equilibrium. Next, the complexity of the general model can be reduced by deleting statistically insignificant variables, or equally, imposing acceptable restrictions, to obtain a “congruent” model. That is, the final parsimonious model should be able to adequately characterize the empirical evidence within the proposed theoretical framework. The resulting model is subject to a series of diagnostic checks through an extensive analysis of the residuals and predictive performance in order to identify any weakness obtained in the preceding step, and restrictions are accepted only if they pass diagnostic checks.44 These include satisfying evidence against non-normality, serial correlation, heteroskedasticity, model misspecification and structural instability.

The performance of this modelling technique has recently been assessed for its ability to recover the DGP through a Monte Carlo study by Hoover and Perez (1999).

44 See Hendry and Richard (1982), Gilbert (1986), Ericsson, Campos and Tran (1990), Charemza and Deadman (1992), Hendry (1995) and Campos, Ericsson and Hendry (2005) for more detailed expositions on the general-to-specific modelling technique.

They find that the technique is able to recover the correct specification, or a closely related specification, most of the time. Extending their investigations to cross-section datasets, Hoover and Perez (2004) find an equally impressive performance for this technique.

4.5 Conclusions

This chapter discusses the data sources and the construction of variables that will be used in this study in order to set the stage for the ensuing empirical analyses in Chapters 5 to 9. The Autoregressive Distributed Lag (ARDL) bounds procedure is proposed as the cointegration test. The unrestricted error-correction model is adopted, which accounts for omitted lagged variable bias. To estimate the long-run relationship, an instrumental variable technique is used so that reliable inference can be drawn from the estimates. The general-to-specific modelling technique is used to simplify the conditional error-correction model. In order to test the robustness of the results and to facilitate their interpretation, all estimations are subject to various diagnostic tests.

Chapter 5: Financial

deepening

and Its

Determinants

5.1 Introduction

This chapter seeks to examine the determinants of financial deepening in Malaysia, with a focus on how real output and financial policies affect financial deepening. Financial deepening is measured by the ratio of private credit to GDP and the ratio of M2 to GDP. To measure the effects of financial sector policies, two different measures are proposed - real interest rates and an index of financial liberalization.

As part of the emergence of the new theories of endogenous economic growth over the past two decades, there has been a surge of interest in the potential role played by financial deepening in economic development. As discussed in the literature review of Chapter 2, the finance-growth empirical literature is dominated by cross-country analyses. With few exceptions, these studies have consistently shown that financial deepening has a beneficial impact on economic growth. Importantly, most studies have ignored the possibility of reverse causation in the finance-growth nexus. When financial deepening is specified as the dependent variable instead, the country case studies evidence of Demetriades and Luintel (1997, 2001) show that economic development has a positive impact on financial deepening. Hence, although the positive correlation between financial deepening and economic growth is already a stylized fact as verified by many empirical studies, an important and yet somewhat under-researched issue is what determines financial deepening?

Development of the financial system is shaped by financial sector policies. Despite liberalizing interest rates in 1978, the Malaysian financial system continues to operate within the context of repressionist policies through the provision of subsidized credit to certain priority sectors.45 This chapter addresses the important question of how the effects of government intervention in the financial system have affected development of the financial sector. This question is of significant relevance for the formulation of financial sector policies.46

Empirical studies of the effects of financial sector policies on financial deepening have typically used real interest rates as the proxy for financial liberalization, 45 See Chapter 3 for more details.

46 For in-depth case studies on financial liberalization in developing countries, see Cheng (1986), Kohsaka (1987), Park (1994), Yusof, Hussin, Alowi, Lim and Singh (1994), Demetriades and Luintel (1996, 2001), Thirl wall and Warman (1997), Sen and Vaidya (1999) and Ariff and Khalid (2000).

where a rise in this measure implies greater liberalization in the financial sector.47 However, real interest rates may be affected by a number of factors other than changes of policy environment in the financial system, rendering it an inadequate measure of financial liberalization. In a cross-country analysis, where real interest rates are averaged over a long period of time, this problem may not be severe. However, for a country case study in which the time dimension is important, the use of real interest rates as the sole proxy for the level of financial liberalization can be misleading. As De Gregorio and Guidotti (1995) put forward, higher interest rates may reflect a lack of confidence in economic policy and the banking system, or the adoption of a more risky behaviour in investment undertakings, rather than greater financial liberalization. Furthermore, financial liberalization is not restricted to changes in interest rate policies. In the light of these concerns, an index is constructed using the method of principal component analysis to provide a summary of the joint influence of financial policies. This index captures information on various types of financial restraints imposed on the financial system of Malaysia, including interest rate controls, reserve and liquidity requirements and directed credit programs, to measure the extent of financial liberalization.

The chapter proceeds as follows. Section 5.2 provides the motivation of this analysis. Section 5.3 discusses the analytical framework. Data are described in section 5.4. The estimated results are presented and analysed in section 5.5, and the last section summarizes the results.