Exogeneity and the export-led growth hypothesis: the case of China.

• Author: Kwan, Andy C.C.

1. Introduction

   During the past two decades, many empirical studies such as Balassa [3, 4], Emery [7], Fajana [11], Feder [12], Maizels [21], Rams [22, 23], Tyler [26], Voivodas [27], Williamson [28], and others have found that exports promote economic growth. In all of these studies, a real output growth variable is regressed on either (i) export levels, (ii) export shares or (iii) export growth by using a single-equation model. The statistical significance of the (positive) coefficient of the export variables has then been interpreted as evidence supporting the export-led growth hypothesis.

   Chow [6], Hsiao [16], and Jung and Marshall [17] have recently questioned the validity of the above findings. This is because the single-equation (or so called "impact") studies using OLS regression are, from an econometric perspective, mostly inadequate in addressing the issue of causality. If a bidirectional causality between these two variables (exports and output) exists, the estimation and tests used in the impact studies are inconsistent. These concerns have subsequently generated a series of new empirical work aimed directly at resolving the issue of causality between exports and output growth [1; 2; 14; 20]. The Granger [15] causality tests carried out in these studies have revealed that the causal direction, in general, depends on the country and commodity group under consideration.

   Notwithstanding the important contributions of the above mentioned causality studies, there are shortcomings that must be dealt with to permit a better understanding of the subject matter. First, the impact studies presume that the export variable is exogenous. This is a rather restrictive assumption as a feedback from output to exports is very likely [17; 20]. Second, the existing causality studies do not make a clear distinction between "exogeneity" and "causality". As suggested by Engle, Hendry and Richard [10, hereinafter EHR], causality tests, such as the Granger [15] method, are valid only for testing one component of "strong" exogeneity because they are concerned with sequential marginalizing feedback effects, rather than contemporaneous conditioning upon which (weak) exogeneity is crucially based.(1) Thus, the presence of Granger's causal relationship is neither a necessary nor a sufficient condition for any discussion on export-promotion policies.

   In this paper, we argue that these shortcomings should be dealt with by carrying out formal exogeneity tests under a framework proposed by EHR. The three distinct concepts of exogeneity (weak, strong and super) will directly address the issues of (i) validity and efficiency of existing impact studies estimates, (ii) whether export growth helps forecast output growth, and (iii) whether the relationship between export growth and output growth is structurally stable and invariant to policy interventions.

   In line with the above, an analysis of exogeneity will be applied to newly released statistics from the People's Republic of China for the period 1952-85. We choose China as the focus of our study because Kwan and Cotsomitis [20] have recently found that the size of the Chinese export sector Granger causes its economic growth.(2) Since the concepts of "causality" and "exogeneity" are different, it would be of considerable interest to extend their analysis by employing the EHR exogeneity framework. In addition, recent economic data from China indicate that national income and exports rose 11.6 and 30 times respectively during our sample period. In light of the parallel growth in these two variables, it is important to examine the validity of the export-led growth hypothesis in the case of China. In particular, our super exogeneity test results may shed some light on the policy implication of this hypothesis.

   The remainder of this paper is organized as follows. Section II presents the econometric methodology, the data used and the model specification. Section III reports our empirical results. Section IV offers some concluding remarks.

2. Econometric Methodology, Data and Model Specification

   If the export-led growth hypothesis is to be tested, then there must be a causal relationship posited of the form:

   [Mathematical Expression Omitted]

   with output growth D[Y.sub.t] and export growth D[X.sub.t].(3,4,5) This specification admits an AR(k) process for DY, current and lagged effects of export growth, as well as other variables [w.sup.t] to enter the relationship. The vector of coefficients is given by [Alpha]; that the subset of coefficients [Mathematical Expression Omitted] whose sum should be positive for export-led growth.

   Most empirical studies of the export-led growth hypothesis only explore special cases of (1). The "impact" studies typically ignore the dynamic structure of the variables and focus exclusively on the contemporaneous relationship between DX and DY. The causality studies, on the other hand, pay close attention to dynamic specifications but omit either the potential influence of other variables or the effect of current export growth on output growth.(6) As is well known in econometrics, inadequate exploration of dynamic specification and omitted variables may lead to erroneous inferences. In order to avoid these shortcomings, we adopt a general functional form like (1) which allows not only for current and lagged effects of export growth(7) but also for other variables that are likely to influence output growth.

   Including D[X.sub.t] in (1), however, poses a potential problem, namely that the current export growth variable may not be exogeneous. This will be the case if (1) is part of a simultaneous system of structural equations or if the "growth-caused exports" [17] is indeed the...