Does economic policy uncertainty dampen imports? Commodity-level evidence from India
Introduction
Frequent and sudden economic policy changes are considered to be one of the main hurdles for business operations in developing economies. Despite having some crucial economic and business implications of policy uncertainty, it is quite challenging to measure it precisely. Lately, Baker et al. (2016) have developed an index of economic policy uncertainty (EPU), which is suitable and convenient to quantify its impact on the indicators of the economy. This research is part of a developing literature on the real effects of policy uncertainty on economic indicators. In this study, we specifically focus on the effects of policy uncertainty on commodity – level imports to an emerging country, i.e., India.
The background work of measuring the impact of economic policy uncertainty on the economy was initiated almost four decades ago by Marcus (1981), which attempts to analyze the effects on policy uncertainty on technological innovation. Bernanke (1983) tries to show the impact on investment through a theoretical model. Aizenman and Marion (1991) and Rodrik (1991) further extended the discussion and evidence. A series of recent empirical research attempted to examine the effects of economic policy uncertainty on investment, tourism, oil price and financial markets (e.g., Kang, et al., 2014; Antonakakis et al., 2014; Aloui et al., 2016; Gozgor and Ongan, 2017; Jens, 2017; Sharma, 2020).
To the best of our knowledge, there is very limited empirical literature that has examined the nexus between economic uncertainty and trade. For instance, the model of Novy and Taylor (2014) shows the effects of a direct channel of policy uncertainty on imports. In an open economy setting, firms have option to procure either domestic or foreign intermediate inputs. If a situation of relatively high level of economic uncertainty prevails, then firms are likely to reduce their dependence on foreign inputs and use more domestic ones since inventory costs are higher for imported inputs, leading to imports contraction. However, the argument may not be valid in all cases. In some situations, the uncertainty may dampen inputs market and domestic investment, which could lead to more reliance on imports. Thus, uncertainty situations can boost imports. While focusing on trade policy uncertainty, Handley and Limao (2015) show that the uncertainty severely affects firms exporting behavior. A range of studies has also shown that policy uncertainty seriously affects investment, income and makes exchange rate and inflation volatile, which may affect firms’ and consumers’ demand for the imported items.
Against this backdrop, in this paper, we examine the effects of economic policy uncertainty on Indian imports. We use a panel of 97 commodities that were imported during the period from September 2011 to January 2019 in the analyses. To test the robustness of the results, we also examine the effects using aggregated import data at a quarterly frequency. The use of aggregated data allows us to cover a longer time-horizon. We contribute to the existing literature in a variety of ways. First, we choose to examine the effect on imports. Notably, the imported inputs have become the primary source of growth for exports in developing economies like India in recent years. The results of Hummels et al. (2001) demonstrate that the vertical integration of imported inputs constitutes almost 21 per cent of exports of the emerging world. Results of Anós-Casero and Astarloa (2010) show that the value addition of imported products was around 14.5 percent in overall exports of Argentina in the year 1997. In a similar line, Turco and Maggioni (2013) for Italian industries, and Aristei et al. (2013) for European economies, establish a vital reliance on imported inputs for their exports. Among other researchers, Sharma (2014) has shown the highest level of dependency for export and total factor productivity (TFP) growth on imported inputs in the context of India.
Second, for analysis, we mainly opt to use commodity level data than the aggregated import data because this approach provides more precise information through heterogeneity in imported data regarding the linkage of import flows with policy uncertainty. Third, we employ Autoregressive Distributed Lag (ARDL) cointegration based method in the panel context. This helps in findings the long-run as well as short-run effects. This is important because it can be argued that the uncertainty may not have long-run consequences as it may settle down in the long run. However, some other authors do not support this viewpoint and believe that uncertainty has both short and long-run consequences (e.g., see Fang et al., 2018; Sharma, 2020).
Furthermore, the issue of error cross-section dependence is overlooked in these models. The assumption related to errors that they are independently distributed may lead to wrong and inconsistent inference estimates if the data is suffering from error cross-section dependence. Therefore, we also employ the CS-DL (asymptotic distribution of the cross-sectionally augmented distributed lag) approach of the mean group. This approach relies on pooling cross-section with dependency and large time-series data under the coefficient of heterogeneity. Fourth, several previous studies have used annual data in their analyses, while the EPU index is developed to display the short-time horizon uncertainty more suitably. A long-horizon analysis using lesser frequency data, such as annual, might not capture the effect as the short-run deviations are often settled down in the low-frequency data. Therefore, we use monthly commodity-level data for examining the effects, which is likely to provide some better insights. Given these arguments, our paper is expected to make a significant contribution to the literature and offers valuable policy insights for emerging economies like that of India. Finally, imports can be potentially affected by both domestic and global shocks. Unlike previous studies, we use a range of uncertainty indicators both at the domestic and global level to test their effects on Indian imports. Recently some studies, e.g., Ludvigson et al. (2020), have shown that market uncertainty can have severe implications for output and trade. With this viewpoint, we also examine the market uncertainty impact on imports.
The rest of this paper is organized as follows: the next section offers a brief review of the existing literature. In section 3, we discuss import and policy issues and offer some stylized facts in the context of India. Section 4 reports the nature of data and measurements. Section 5 outlays the econometric specification and its relevant discussion. In Section 6, we present results and their related discussion. The final section concludes with plausible policy implications.
Section snippets
Literature review
As discussed in the introduction section, recently there have been several empirical studies which explored the effects of economic uncertainty on real economic activities (see, e.g., Kang et al., 2014, 2017; Pástor and Veronesi, 2012, 2013; Tam, 2018; Sharma, 2020; Xu, 2020). However, not many researchers have tested their effects on international trade. There are some studies, which focused on how the shocks in economic policy uncertainty affect exchange rate fluctuations (Krol, 2014) and
Imports and policy uncertainty in India
The import policy of India was suffering from quantitative restraints as well as a high level of import tariff structure before 1991. The import tariff structure was characterized by an extreme-level of tariff and quota on final goods. However, intermediate and primary imports were relatively less taxed. This type of inward-looking and import substitution policy was a major impediment for the growth of the industrial sector in the country. A range of drastic economic reforms and liberalization
Data
This research utilizes unit-level monthly frequency data of 97 merchandized items imported to India. Almost all merchandized sectors’ imported commodities data are used in our analysis. This includes agriculture, ores, minerals, petroleum, crude, chemicals, textiles, engineering goods, leather and several other types of raw, processed and manufacturing goods. We retrieve monthly data series on quantity and unit price of these items (mp) from ‘Economic Outlook’ database that is made available by
The model
Conventional theoretical models of import demand equations (e.g., Emran and Shilpi, 1996) consider variables such as price of imported commodities, destination country’s income or output, which is usually proxied with GDP, price level at source country and the destination country and rate of foreign exchange between source and destination country. Since India’s contribution to the world’s total imports is not very large; so it may be realistic to assume that imports to India are somewhat
Analysis of commodity-level panel data
Before we run the regression analysis, it is important to identify the order of integration of the variables. For this purpose, we employ a panel unit root (Levin et al., 2002) test, which works under the assumption of ‘common unit root processes’. The null hypothesis of unit root is tested against the alternative hypothesis of no unit root. The results from the panel unit root test, see Table 2, establish that the selected variables follow a random walk behavior. These evidences, therefore,
Conclusion
This research paper was aimed to investigate the role of economic uncertainty on commodity-level imports to India during the period of September 2011 to January 2019. To achieve our objective, we undertook two estimation techniques, such as the PMG and CS-DL. By making use of these econometric techniques in panel data context, our study established that the economic uncertainty and commodity-level imports, along with control factors, share a significant long-run equilibrium relationship during
Declaration of competing interest
There is no conflict of interest to report.
Acknowledgement
We sincerely thank Prof Angus C. Chu, Co-Editor of this journal and two anonymous reviewers for their constructive and very useful feedback on previous versions of this paper.
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