Export Volatility Research Articles

Factoring in the Micro: A Transaction‐Level Dynamic Factor Approach to the Decomposition of Export Volatility

This paper analyzes the export volatility sources estimating a dynamic factor model on transaction‐level data. Utilizing an exhaustive dataset of French export transactions from 1993 to 2017, we reconstruct the latent factors space associated with global and destination‐specific macroeconomic shocks through a Quasi‐Maximum likelihood approach which allows accommodating both the high share of missing values and the high dimensionality of the microeconomic time series. The estimated parameters are then used to derive a volatility decomposition of the aggregate and firm‐level export growth rates, highlighting structural spatial patterns and the role of geographical diversification in mitigating export risks.

The Impact of Export Volatility on Economic Growth in Algeria during 1992-2016: An Econometric Study

Objectives: The issue of export volatility in the economies of less developed countries (LDCs) is a significant topic of debate in economic literature. This paper aims to investigate the potential effect of export volatility on economic performance in Algeria. Methods: The study utilizes an econometric model to estimate the impact of export volatility on economic growth in Algeria for the period 1992-2016. Additionally, another regression model is used to analyze the effects of fluctuations in export prices and quantities on economic growth in Algeria. Results: The findings show that there is no significant relationship between the export instability index and real GDP. Conclusion: The study concludes that fluctuations in the prices and quantities of exports do not influence Algeria’s real GDP. Policymakers should reduce the dependency of the export sector on oil products and improve industrial performance in Algeria. Implementing price stabilization schemes and allocating more oil precautionary funds are also needed to mitigate any possible damaging effects of export volatility on Algeria’s economy in the future.

Can Export Market Diversification Mitigate Agricultural Export Volatility? A Trade Network Perspective

ABSTRACT Using the social network analysis (SNA) method to calculate the level of agricultural export market diversification in various countries, this study examined the impact of agricultural export market diversification on export volatility from the supply network perspective based on HS6-digit agricultural export data. We identified that the agricultural export market diversification significantly reduces the export volatility. Specifically, the effect of diversifying the export market of processed agricultural products in stabilizing export volatility is greater than that of primary agricultural products. The stabilizing effect of emerging markets and developing countries or regions is more evident than developed countries or regions. Moreover, the export market diversification can stabilize the volatility of agricultural exports through two mechanisms: increasing the international market share and extending the export duration.

Forecasting the Impact of the COVID-19 Outbreak on China’s Cotton Exports by Modified Discrete Grey Model with Limited Data

The sudden outbreak of COVID-19 has created dramatic challenges for public health and textile export trade worldwide. Such abrupt changes are difficult to predict due to the inherently high complexity and nonlinearity, especially with limited data. This article proposes a novel modified discrete grey model with weakening buffer operators, called BODGM (1,1), for forecasting the impact of pandemic-induced uncertainty on the volatility of cotton exports in China under limited samples. First, the Mann–Kendall test examines how pandemic-induced uncertainty affects cotton exports, based on China’s monthly cotton export data from June 2014 to August 2022. Second, buffer operators are employed to weaken the nonlinear trends and correct the tentative predictions of the discrete grey model. Then, the BODGM (1,1) model was validated by comparison with four alternative models. The results indicate that the BODGM (1,1) model was particularly promising for identifying mutational fluctuations in cotton exports and outperformed the GM (1,1), DGM (1,1), ARIMA and linear regression models in fitting and prediction accuracy under volatility and limited data. The BODGM (1,1) model forecast results for China showed that cotton export volume was expected to show signs of recovery over the next 12 months. The findings of this study may provide a basis for formulating trade policies to mitigate the impact of the COVID-19 outbreak on export resources and build their resilience to future pandemics.

The Causes of Export Volatility in Algeria during the Period of 1992-2016

This paper aimed to investigate the drivers of export volatility in Algeria and to estimate the impact of export structure and product concentration exports on export volatility in Algeria via a regression model using annual time series data for the period 1992-2016. The results showed that the high export volatility in Algeria was mainly caused by the increase in the share of exports of consumer goods and raw materials and the continuous increase in exports. The paper concluded that there is a need to reduce reliance on primary exports in Algeria. Therefore, policymakers should work on diversifying the exports to reduce the export volatility in Algeria.

Managerial Ability, Earnings Quality, and Future Performance

This paper investigates Algeria's main export volatility drivers via a regression model. The methodology involves the construction and estimation of an econometric model. In this model, the annual time series from 1992 to 2016 is used to estimate the impact of export structure and product concentration on the size of export volatility. The results reveal that export volatility in Algeria is high, and this is due to the growing percentage of consumer and raw material exports. The increasing size of exports is also an essential determinant of volatility. The findings indicate a need to reduce the reliance on primary exports while policymakers should diversify the export basket to reduce export volatility.

The Impact of Crude Oil Prices on Macroeconomic Factors in Korea

Purpose - The purpose of this study is to examine how Korea’s macroeconomic factors, such as GDP, CPI, Export, Import, Unemployment rate and USD/KRW exchange rate, are affected by the oil price shocks. Design/methodology/approach - This study used monthly and quarterly time-series data of each variable for the period 1983 to 2022, consisting of two sub-periods, to employ Granger causality test and GARCH method in order to identify the role of the oil price movement in macroeconomic factors in Korea. Findings - Korea’s currency rate to the US dollar is negatively correlated with the price change of crude oil while the GDP change is positively correlated with the price change of crude oil with strong relationship between Export and Import in particular. The exchange rate and GDP growth are believed to be not correlated with the oil price change for the pre-GFC period. According to the Granger causality test, the price change in crude oil has a causal impact on CPI, Export and Import while other factors are relatively slightly affected. Transmission effect from the oil price to Export is found and there also exists volatility spillover from oil price to economic variables under examination. Comparing two sub-periods, CPI and Export volatility responds negatively to shocks in the oil price for the pre-GFC period while volatility of CPI and Unemployment reacts positively to the oil price shocks for the post-GFC period. Research implications or Originality - The findings of this study could be helpful for both domestic and international investors to build their portfolio for the risk management since rising WTI price can be interpreted as a result of global economic growth and ensuing increase in the worldwide demand of the crude oil. Consequently, the national output is expected to increase and the currency is also expected to be strong in the long run.

The impact of exchange rate changes on the Japanese chemical industry

We investigate how exchange rates affect the Japanese chemical industry. This industry exports sophisticated products to downstream firms. Since more complex products are less substitutable in international trade, we investigate whether they have lower price elasticities. We measure complexity using Hidalgo and Hausmann’s (2009) product complexity index. We find that price elasticities are lower for more complex chemical goods. We also find that stock returns of chemical firms that occupy vital niches in the world economy are harmed less by yen appreciations. These results indicate that exporting sophisticated products can reduce export volatility and profit volatility arising from exchange rate swings.

The COVID-19 pandemic, consumption and sovereign credit risk: Cross-country evidence

Many recent studies investigate the economic effect of the COVID-19 pandemic in multiple aspects, while whether and how the sovereign credit risk reacts to the shock is still underexplored. Using a sample of forty developed and developing countries and employing staggered difference-in-differences models, we find that the sovereign credit risk measured by sovereign credit default swap spreads significantly increases after the COVID-19 pandemic outbreak, and the adverse effect is more pronounced for short-term credit risk. The reason is that the pandemic causes severe concerns about aggregate consumption contraction in addition to the fiscal capacity and the volatility of exports. We also find that fiscal stimuli stabilizing consumer spending alleviate the adverse effect of the COVID-19 pandemic, while debt relief does not matter. Overall, practitioners and policy makers should attach more importance to consumption and its recovery during the pandemic when making decisions.

“Asymmetric Export Volatility Shock Behaviour” of Lower Middle Income (LMI) Countries in South East Asia During COVID-19 Pandemic

COVID-19 Pandemic still affecting all countries. South Asian economies and that particularly India is no exception. Because of this “uncertainty shock”, India’s GDP has contracted by 3.1percent in the last quarter of 2020. The present empirical work covers broadly the “asymmetric spillover and related noisy shocks” surrounded with trade (export) volatility about LMI nations in “two phases” i.e. in terms of considering the During pandemic phase (DC) the period from April 2019 till June 2020 and Pre-pandemic phase (PC) from April 2013 till November 2020. A comparative trade volatility asymmetries analysis were applied using a nonlinear volatility function i.e. exponential weighted moving average (EWMA), and identification of noisy behaviour after the initial post-recovery for empirical evidence. The empirical findings discovered that there were “extended” non-smooth and noisy “shock propagation” post initial recovery across two phases by the use of VAR and VECM outcomes. Bangladesh and Pakistan were stronger “Noisy shock contributors” while Nepal and Sri Lanka were turned out to be the strongest “Noisy shock receivers”. This “noisy” behaviour implies “uncertainty” and chaos on the international trade front resulting in higherthan expected volatility in trade figures and in-built destabilized momentum in the impulses. The results also relate to the possible opportunities of intra-regional trade convergence as a policy imperative.

Exchange rate uncertainty and cereals exports: A panel VAR approach

This paper empirically investigates the effect of exchange rate uncertainty on cereals export flows for a broad sample of 75 countries during the 2010/01 - 2016/12 period. To do this, we first estimate the exchange rate volatility, and then, we estimate the cereals export demand by using a panel data model with autoregressive vectors (P-VAR). This strategy of analysis is applied over different groups of countries, which are obtained by cluster analysis based on the level of exchange rate volatility and the volume of cereals exports. The empirical results suggest a significant negative effect of exchange rate uncertainty on cereals exports in countries characterized by high and persistent exchange rate volatility or high volume of cereals exports.

Export volatility with trade policy uncertainty: Evidence from China*

AbstractThis paper studies the effect of trade policy uncertainty on firm‐level export volatility. Using data on Chinese exporters around China's WTO accession, we find that a reduction of trade policy uncertainty between China and the United States decreases the volatility of firm‐level export to the United States and increases the volatility of export to the rest of the world. In the aggregate firm level, this shock in trade policy uncertainty has no significant effect on the volatility of total export or the volatility of total sales. Our finding suggests a risk‐sharing effect among export destinations.

Time‐varying impact of global, region‐, and country‐specific uncertainties on the volatility of international trade

AbstractWe use a dynamic factor model with time‐varying parameters and stochastic volatility to decompose the variance of exports and imports over time for 22 Organization for Economic Co‐operation and Development countries spanning the quarterly period of 1960:01–2016:04 into contributions from country‐ and region‐specific uncertainties and uncertainty common to all countries. We find that, while idiosyncratic uncertainty has a dominant role in explaining the volatility of international trade, global, country‐, and region‐specific uncertainties drive around 40% of the volatility of real exports and imports, with the impact of the latter three uncertainties rising in explanatory power during episodes of crises. Our results have important policy implications.

Trade Volatility in the Association of Southeast Asian Nations Plus Three: Impacts and Determinants

This paper investigates trade volatility in the Association of Southeast Asian Nations Plus Three (ASEAN+3) and its links with output volatility, export diversification, and free trade agreements. To achieve this research objective, we apply several econometric estimators to data from all ASEAN+3 member states over the period 1990–2016. We first find evidence of a positive relationship between output volatility and trade volatility. Second, we reveal that the way export diversification is measured can influence its impacts on bilateral export volatility. Moreover, the relationship between income volatility, trade volatility, and export diversification seems to depend on country size and the level of economic development.

An Approach of Reducing Overall Level of Export Fluctuations of the Export-oriented Countries

Overall level of export fluctuations of the export-oriented countries with rising export volume partly stem from the market failure caused by free choice of export enterprises, some government intervention thus may be necessary. To reduce the level of fluctuations of the export growth rates in these countries, this paper, taking the significant differences of the exports among various markets into account and thus using a new index named relative variance to measure the export volatility risks, proposes a model of merchandise market portfolio, a modified version of Markowitz model, available to provide explicit guidelines for the firms, the industries and even the whole country to optimize the structure of their export markets. An application of this model to the case of China's apple is then discussed. The results show that the market share of China’s apple in 7 sub-markets should be redistributed drastically.

The impact of exchange rate volatility on Indonesia's top exports to the five main export markets

This study examines the impact of exchange rate volatility on Indonesia's primary export commodities to the top five export destination countries, namely China, India, Japan, South Korea, and the United States. This study uses a GARCH model to obtain an estimated value of exchange rate volatility, using monthly data covering from 2006 to 2018. The ARDL method helps to measure the effect of exchange rate volatility on exports to destination countries in both the short and the long-term. Aggregate exports are compared employing a linear (ARDL) and a non-linear autoregressive distributed lag model (NARDL). The findings suggest that exchange rate volatility has a significant effect on exports of commodities under code 26 (ores), 38 (chemicals), 40 (rubber), and 47 (pulp paper) to India, Japan, South Korea, and the United States, either in the short or long-run. The exchange rate volatility of exports to China only affects plastics goods (code 39), although many goods experience negative effects due to exchange rate depreciation. In India, exchange rate volatility affects the largest number of export commodities. The Index of Industrial Production (IIP) has a strong long-term effect on exports to Asian countries. Impacts due to exchange rates offer both negative effects and positive effects (expected) in exports at commodity and trade partner case-to-case levels. Both aggregate ARDL and NARDL models suggest that Indonesian exports are negatively affected by exchange rate fluctuations.

Time-Varying Model for Non-Oil Export Volatility in Nigeria

Time-Varying Model for Non-Oil Export Volatility in Nigeria

Input–Output Linkages and Sectoral Volatility

Why are some sectors more volatile than others? This paper uncovers evidence of an empirical regularity in the US economy: upstream sectors that are far removed from final consumers have higher levels of output volatility. The relationship between volatility and upstreamness is not driven by sector size, sector concentration, trade openness or the level of aggregation at which sectors are defined. Rather, the paper shows a stronger link between upstreamness and nominal output volatility, than with indexes of real output volatility. Aggregate exports at the national level also reflect the empirical regularity of higher volatility with upstreamness: Export volatility is higher in economies with trade portfolios dominated by upstream sectors. On average, reducing the upstreamness of exports by 1 also reduces aggregate export volatility by about 10%. The pattern of higher volatility for upstream sectors is explained with a model of demand shock transmission between sectors.

An Analysis of the Trend of China’s Export Trade to the USA Based on R Language

After President Trump came to power, in order to change the “imbalance” between China and US trade, he launched a trade war with China, which led to increase uncertainty in China-US trade and increased export volatility. Based on R language environment, this paper compares the advantages and disadvantages of seasonal ARIMA (p, d, q) model and double-index ETS (A, N, A) model in short-term forecast of China’s total export value to the United States. Then, the double-index ETS (A, N, A) model is selected to predict the trend of China’s export trade to the United States in the months of 2009-2020. The forecast results show that China’s export to the United States has seasonal characteristics. The export fluctuation is smaller than that in 2018, but the total value of exports has decreased significantly. Finally, some suggestions are put forward.

Input-Output Linkages and Sectoral Volatility

Why are some sectors more volatile than others? This paper uncovers evidence of an empirical regularity in the U.S. economy: upstream sectors that are far removed from final consumers have higher levels of output volatility. The relationship between volatility and upstreamness is not driven by sector size, sector concentration, trade openness or the level of aggregation at which sectors are defined. Rather, the paper shows a stronger link between upstreamness and nominal output volatility, than with indexes of real output volatility. Aggregate exports at the national level also reflect the empirical regularity of higher volatility with upstreamness: Export volatility is higher in economies with trade portfolios dominated by upstream sectors. On average, reducing the upstreamness of exports by one, also reduces aggregate export volatility by about 10%. The pattern of higher volatility for upstream sectors is explained with a model of demand shock transmission between sectors.