Foreign Trade is an external sector globally as a huge potential key driver of economic growth rate, income equity and poverty reduction. Since the 1990s, South Asia has struggled with trade gain from internationalism and regionalism by building a liberal trade policy regime.
SAPTA (South Asian Preferential Trading Arrangement) to SAFTA (South Asian Free Trade Area) is an example of intra and inter regionalism within SAARC (South Asian Association for Regional Cooperation) to improve trade share to 42 trillion international trades and to catch up 7% of Global GDP in SAARC through preferential trade and lowering tariff.
However, empirical and theoretical literature shows less than 5% intra-regional trade in the mutual trust deficit induced tariff and non-tariff barrier and protectionism, no trustworthiness of trade flows, higher cost of connectivity and no strong trade bonding, although multilateralism and regionalism have triggered to improve value and volume of trade of SAARC member countries. Its output is negligible trade outcomes to developing and least developing member countries in SAARC, but the growth of trade dependency is interestingly impressive. One example is Nepal.
In Nepal, about 6.5% average growth miracle was recorded in the last 3 consecutive years from 2016, 2017 and 2019 (ADB, 2019, WB, 2019 & MoF, 2020). Such appreciative miracles have bounced back with the desired growth confidence and hope trigger in the economy for achieving the national development goal of “happy Nepali, prosperous Nepal” within the next 20 years. It was a surprise in mathematics in growth economics.
Its reasons were underperformance of agricultural growth, industrial growth and imbalance growth of trade sector but over the performance of remittance led household consumption (29% of GDP). However, these pillars’ validity and significance could not be ignored. Therefore, the uncontrolled growth of import trade led trade imbalance has mixed outcomes in the national economy.
In macroeconomy, it is an unstable creator with the ₹1300 billion trade deficit as the cost of export trade, but the import of raw materials and capital goods and services have positive outcomes to strengthen and expansionary productive sectors and construction of big projects: hydro and road and to create employment opportunities, resources and products.
Trade of Nepal is still a magic box of the paradox between expectation and reality. In 2020, the trade-GDP ratio was 52% out of which export GDP ratio was 9.8%. Meanwhile, import GDP ratio was 42%. As a result, the import-GDP ratio is excessive to export-GDP ratio.
In other words, trade deficit-GDP ratio is 32.2%. It is greater than remittance-GDP ratio (29%). In the figure, trade volume is recorded ₹1992 billion (MoF,2020). In the trade statistics, Nepal has traded with 119 countries of the world out of which the trade statistics indicate 20 countries as major trade partners.
Despite 20 major trade partners, Indo-Nepal and Sino-Nepal trade are dominants with 65% and less than 5% respectively in the trade structure. As a result, trade openness and liberalisation have not improved trade diversification and benefits as the target goal of Trade Policy 1996 and 2009 and National Five Years Plans (MoIT, 1996, MoIT, 2009 and NPC, 2019). Its evidence is a huge trade deficit figure and rule in the trade.
In simple, import shares are 94% and export shares only 6%. It indicates the growth of trade dependency and the degrowth of trade independence and lower elasticity of export trade. Its result in trade deficit-GDP is 32% out of which Indo-Nepal trade deficit is 21% and then the rest is 11%. Similarly, the figure for export-import ratio shows 1:16 in Indo-Nepal Trade and 1:44 in Sino-Nepal.
Content analysis in import and export shows a higher variation of values between exported items and imported items. Nepal traditionally exports unprocessed agro products and handicrafts (cardamom, jute goods, textile, polyester, handicrafts and juice) having low value, low competitive capacity and quantities. Meanwhile, import content is essential and industrial finished products: petroleum products, vehicles, machinery, electronics goods, medicine etc. having high value and large quantities.
It indicates a trade trap between India and China and poor trade openness of both countries to Nepal, although they have provided a preferential treatment. Therefore, trade openness and liberalisation have deepened the crisis of trade deficit, trade dependency and domestic productivity. However, its inclusiveness is mentioned in the country’s economic growth, despite its 1.42 trade multiplier.
It does not mean a protective trade policy, regime and philosophy. The reflection of Ancient and Medieval outward trade policy, regime and philosophy can be found during the regime of the first Rana Prime Minister Jung Bahadur Rana. After, Nepal adopted trade openness to foreign products and services in the domestic market (Bista, 2016).
In the period 1960 to the 80s, import trade was restricted from tariff and non-tariff barriers (higher tariff, quota and high subsidy) to protect the domestic industries and generate revenue resources for development and regular expenditure in the narrow tax base and lower tax elasticity and buoyancy. Its side effect was a macro-economic crisis with 5% current account deficit, 10.7% budget deficit and 13% inflation in the 1980s (Bista, 2016).
Nepal had a question of stability and growth. The World Bank and IMF had recommended a Structural Adjustment Program (SAP) to liberalise the Nepalese economy. As a result, trade liberalisation policy would be executed to some extent. Its full-fledged liberalisation was implemented in the 1990s after the effects of SAP II.
As follow up, SAPTA-SAFTA was signed in 1993 for regionalism. It was supplemented by Gujural Doctrine in 1996 with a unilateral preferential concession to neighbour countries in trade. Its reflection in trade policy, regime and philosophy can be found till date.
In recent years, it is curious to see whether trade liberalisation has become a counterproductive to the landlocked country Nepal in the growth of trade deficit, trade dependency and contraction of productivity and production and whether trade leakages gravity in Indo-Nepal trade is an unexpectedly heavy load in such growth of trade deficit.
Since lockdown policy as a powerful anti-COVID-19 measure was State induced during the pandemic period to reduce its rapid and wider transmission from individual to the family and then the community. Its strictness to shield international border and halt to transportation system affected all economic sectors, but the trade sector was considered unexpectedly extremely broken.
By and large, the external sector’s deduction in the four sector economies had made all economies closed and isolated economies with undesired and unplanned for a short run. It looked like what classical economist mentioned self-sufficient economies in the ancient and medieval period. Thus, the trade sector was fully and partially halted in the world.
Nepal has endorsed anti-COVID-19 measures: hard and soft. In hard measure, strict lockdown measures were executed from 23 March to 21 July 21, 2020, to reduce the inflow of COVID-19 along with human mobility and goods flow. The Indo-Nepal and Sino-Nepal border and transport were closed down for 2 months.
Then after, the lockdown was internally removed with restriction, but both borders were closed. Again, the lockdown was formally announced by Nepal’s government from 16 August to 7 September, 2020, when the government found higher penetration growth per day of COVID-19 in Kathmandu Valley. On 7 September, it was lifted.
As soft measures: odd-even number system and social distancing for transportation, opening cargo of raw materials, essential goods and capital goods in trade but restricted to the flow of people, closed the School and College physically but digitally opened up and closed temples and restricting public gatherings. Till date, soft measures have been effective.
It is argued that the strict lockdown during COVID-19 had severe impacts on trade sectors. There were assumptions as follows:
Therefore, this study is relevant to test the above assumptions.
The study would examine mainly two issues: whether the impact of the COVID pandemic shock and anti-COVID policy measures on Nepal’s trade will be wider and whether the compensatory policy tools to survive, stabilise, and stimulate the slowdown trade sector will be positive. Its output would be valuable to understand COVID-19, anti-COVID Policy and trade sector relationship and explore compensatory policy to trade sector. It would be valuable literature to academicians and policymakers to discourse seriously and sensitively on the trade sector to reshape and remake it exogenous crisis resilient.
The paper examines the impact of COVID pandemic and anti-COVID policy on the trade of Nepal. Its specific objectives are
Let’s suppose GDP is “Y”. Let’s assume COVID-19 positive cases and anti-COVID policy slow down GDP growth. Let’s expand in the regression model as follows:
Yit = α+βXit+β1 Dit + ε………. (i)
Where, α = Intercept, β = Coefficient of COVID-19 positive cases (Xit), β1 = Coefficient of lockdown and border closure (Xit), ε = Error term, Xit = COVID-19 positive cases, Xit = Lockdown and border closure,
Where, α, β and β1 are parameters and have α>1, 0< β1<1 and 0< β2<1.
This paper used secondary data sets of COVID-19. It includes COVID positive cases and lockdown and border closure across the country from March 2020 to September 2020 collected from WHO websites, along with the case of Nepal and South Asia. Its supplementary data sets related to Nepal was accumulated from Nepalese Government agencies: Ministry of Finance, Nepal Government, National Planning Commission, Nepal Rashtriya Bank and Central Bureau of Statistics.
The analytical tool was SPSS to operate simple regression to estimate coefficient.
COVID in the World:
In September, 2020, U.S.A., India and Brazil, Russia, Spain, France and U.K. led in the COVID fact sheet. Over time, its growth was faster than our expectation. Therefore, the IMF and World Bank (2020) projected $3 trillion loss and recession as its cost with the growth of more than 50% unemployed populations and the growth of more than 50% poverty and vulnerability. Further, OXFAM (2020) predicts its distribution of intensity will be more in developing and least developing countries of Africa and Asia.
COVID in South Asia:
WHO (2020) shows the threat of COVID pandemic in South Asia. Figure 4 shows exposure and vulnerability. However, India, Pakistan, Bangladesh, Afghanistan, and Nepal were in the risk, but Sri Lanka, Maldives, and Bhutan were controlled.
As per the effectiveness of anti-COVID measures in SAARC, its risk and vulnerability level was heterogeneous.
COVID in Nepal:
Nepal was not free from COVID, although there was a gossip that Nepal was a COVID resilient country when COVID cases were sluggish and negligible from 23 March to 21 July, 2020. Figure 5 shows its fast growth from 25 May, 2020 when labour migrants started to return from India, China, Saudi Arab, Malaysia, etc. (WHO, 2020). Then after, its trend like rocketed with geometric growth. In September 2020, it reached 77,817, despite lockdown measures. Thus, Nepal was highly vulnerable.
In this scenario, there were three output indicators: COVID cases, death and recovery. Figure 6 presents lower death rate, but COVID cases were dominant in lockdown I and II, but 80% recovery rate made it comfortable in that COVID crisis.
The COVID pandemic had direct and indirect effects. Also, the effective strict lockdown and border closure as anti-COVID measures’ negative outcomes were expected at macro and microeconomic level including economic growth, employment, sector output and performance, trade and balance of payment (BOP), fiscal deficit, livelihood, poverty, etc.
Figure 7 shows the contraction of transport and communication by -13.25% and then -7.16% contraction of trade compared to the pre-COVID scenario (MOF, 2020). It was followed by hotel/restaurant, government service and industry. Thus, the overall economy slowed down.
Figure 8 shows the huge contraction of import and export trade with India and China from the pre-COVID scenario. Pre-COVID, export and import ratio was 1:14 in Indo-Nepal trade and 1: 44 in Sino-Nepal trade. Post-COVID, its ratio sharply fell in both trades with the huge fall of import trade.
In Indo-Nepal trade, it was 1:8.8 (Figure 9). Its implication was the fall of trade deficit to ₹967.7 billion from ₹1161.2 billion. In Sino-Nepal trade, it fell with ₹40 billion while in Indo-Nepal trade it was ₹100 billion.
Despite its negative implication on the sector and aggregate economy, its positive implication was the soft trade deficit pressure to the current account and capital account and the balance of payment. Similarly, from other SAARC countries, Nepal got a positive balance of payment, improving macroeconomic stability with negative economic growth (Figure 10).
Besides, the observations and facts are as follows:
|Variable||Mean (Standard Deviation)|
|COVID19 (x)||98.2727 (101.48)|
|Lockdown & border closure (D1)||2.9765E2(162.26)|
Table 1 presents descriptive statistics (mean and standard deviation). In column 1, three variables are GDP (Y) as dependent variable and COVID-19 (x) and lockdown and border closure (D) measures as independent variables. Standard deviations of these variables are insignificant from the mean, except lockdown and border closure.
|Dependent variable: Average Real GDP(Y)|
|Lockdown & Border closure (D)||-0.86(0.021)|
|Note: * is <5 percent of P value. Dependent variable: GDP|
Table 2 presents the results of simple multiple regression model in which dependent variable is GDP (Y) and two independent variables are COVID-19 (X) and lockdown and border closure (D) having two parameters: β and β1. In the regression model results, parameter (β) explains the marginal change of COVID-19 cases (x), i.e. change in GDP and change in COVID-19 cases ratio. In other words, change COVID-19 explains to change 1% of GDP. Similarly, parameter (β1) explains whether a 1% change in GDP will be in lockdown and border closure or not.
Considering the econometric model’s above results, they provide sufficient evidence on the share of independent variables: COVID-19 (x) and lockdown and border closure (D) in GDP. In order to minimise the undesired threat of the pandemic and its fast transmission rate, national economy, i.e. real GDP (Y) was directly and indirectly derailed by the pandemic and anti-COVID policy measures.
In the model, the p-value of these two independent variables shows significant and valid. Parameter (β) of COVID shows a negative sign with 0.44 values and parameter (β1) of lockdown and border closure shows a negative sign 0.86. In the result of the model, R2 is 0.99. It explains dependent variable GDP (Y) by 99% from independent variables: COVID-19 (x) and lockdown and border closure (D).
Above results show both independent variables: COVID-19 (x) and lockdown and border closure (D) having a negative relationship with GDP. It means COVID hurt GDP and anti-COVID policy had the side effect of contraction shock to GDP by making zero trade openness and zero mobility of goods and service flow.
The level of the negative impact of anti-COVID policy: lockdown and border closure are more than COVID-19. The anti-COVID policy has negatively contributed 0.86% to 1% marginal change of GDP, but COVID-19 has only 0.44% to 1% marginal change of GDP. Therefore, the anti-COVID policy was disastrous to the trade of Nepal.
In the above empirical results, the pandemic and anti-COVID policy were significantly negative for Nepal’s GDP or sector economy, particularly trade sector by zero trade openness and zero goods and services flow for over 7 months (March to September, 2020). ADB (2020), IMF (2020) and World Bank (2020) projected its side effect as a contraction with 3% negative economic growth towards economic recession.
During the pandemic, the economy had a big pressure to stabilise growth and stimulate the threat of GDP loss and contraction. Therefore, the government of Nepal formulated compensatory policy as follows:
Policy Shock I: Disclosure of Transportation Policy under which emergency and essential goods vehicles and markets were opened up and odd and even number system was made effective to private and public vehicles (MoHA, 2020). Similarly, import and export trade of food and medicine were opened up and human mobility was restrictively permitted.
Policy Shock II: Fiscal and Budgetary Policy were made compensatory in the national budget of Nepal 2020-2021(MoF, 2020). In the budget, the government proposed the compensatory policy as follows:
Policy Shock III: Monetary Policy 2020-2021 was disclosed by the Central Bank of Nepal, Nepal Rashtriya Bank (NRB, 2020). The policy carries the compensatory policy as follows:
Despite the compensatory policy, there would be issues such as the execution of above policies and budget in the lockdown time and uncertainty of recovery, rehabilitation and stimulus. Therefore, there was a curiosity whether these policy shocks would be effective.
This paper analyses the impact of COVID-19, anti-COVID policy, and compensatory policy on Nepal’s trade based on secondary data through descriptive statistics and regression model tools. As a result, COVID-19 infected 44.8 million populations. It killed 1.2 million people of 215 countries globally, where its extreme intensity felt on the U.S.A. and G20 countries and India in South Asia and Brazil in South America.
Subsequently, its economic consequence is a loss of 3.4 % economic growth rate, the worst stock market crash, a loss of 400 million full-time jobs, and a $3.5 trillion GDP loss (IMF, 2020 & UN, 2020). Similarly, in SAARC, Nepal ranks at fourth jumping at 35th of 215 countries globally with 0.165 million affected people, 887 death toll, per day new cases >3000 and recovery rate >74%.
Furthermore, the empirical result is the negative impact of COVID-19 and anti-COVID policy on the national economy, particularly trade. Anti-COVID policy’s impact (0.86) is more severe than COVID-19 (0.44) in the economy. Its output is the most vulnerability to trade: Indo-Nepal and Sino-Nepal.
Its outcomes are mixed: negative to sector economy, employment and economic growth and positive to the trade deficit, trade dependency and balance of payment. The compensatory policy is a stable shock to the negative consequence of COVID-19 and anti-COVID policy.
Therefore, Nepal is vulnerable to COVID-19 and the trade sector is most vulnerable. For survival, stability and stimulation national economy and trade, the compensatory policy should be implemented and anti-COVID policy should be revised.
Excerpts from Raghu Bir Bista in a webinar jointly organised by South Asian Studies Center at IMPRI, Counterview and Centre for Development Communication & Studies (CDECS), Jaipur as part of the series “The State of Economic Development in South Asia – #EconDevDiscussion’ with Prof Utpal K De on “Trade and Policy Shocks in Nepal amid COVID-19 Pandemic: Observations, Lessons and the Way Forward”.
By Raghu Bir Bista