Raghu Bir Bista
INTRODUCTION
Foreign Trade is an external sector in the World as a huge potential key driver of economic growth rate, income equity and poverty reduction. Since 1990s, South Asia has been struggling trade gain from internationalism and regionalism through building a liberal trade policy regime. SAPTA to SAFTA is an example of intra and inter regionalism within SAARC to improve trade share to 42 trillion international trades and to catch up 7 percent of Global GDP in SAARC through preferential trade and lowering tariff. However, empirical and theoretical literatures show less than 5 percent 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 outputis negligible trade outcomes to developing and least developing member countries in SAARC but the growth of trade dependency is interestingly impressive. Its example is Nepal.
In Nepal, about 6.5 percent average growth miracle was recorded in the last three consecutive years from 2016, 2017 & 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 next 20 years. It was a surprise in the mathematics in growth economics. Its reasons were under performance of agricultural growth, industrial growth and imbalance growth of trade sector but over 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 the trade imbalance has mixed outcomes in national economy. In macro economy, it is instable creator with the 1300 billion Rs 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 paradox between expectation and reality. In 2020, trade-GDP ratio is 52 percent out of which export GDP ratio is 9.8 percent meanwhile import GDP ratio is 42 percent. As a result, import-GDP ratio is excessive to export-GDP ratio. In another words, trade deficit-GDP ratio is 32.2 percent. It is greater than remittance-GDP ratio (29%). In the figure, trade volume is recorded 1992 billion Rs.(MoF,2020). In the trade statistics, Nepal has trade 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 percent and less than 5 percent respectively in the trade structure. As a result, trade openness and liberalization have not improved trade diversification and benefits as the target goal of Trade Policy 1996 and 2009 and of 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 94 percent and export shares only 6 percent. It indicates the growth of trade dependency and the de growth of trade independency and lower elasticity of export trade. Its result is trade deficit-GDP is 32 percent out of which Indo Nepal trade deficit is 21 percent and then the rest is 11 percent. Similarly, the figure of export import ratio shows 1:16 in Indo Nepal Trade and 1:44 in Sino-Nepal. Content analysis in import and export shows higher variation of values between exported items and imported items. Nepal traditionally export unprocessed agro products and handicrafts (cardamom, jute goods, textile, polyester, handicrafts and juice) having low value, low competitive capacity and low 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 traps between India and China and poor trade openness of both countries to Nepal, although they have provided a preferential treatment. Therefore, trade openness and liberalization have deepened the crisis of trade deficit, trade dependency and domestic productivity. However, its inclusiveness is mentioned in economic growth of the country, 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 first Rana Prime minister Jung Bahadur Rana. Then after, Nepal adopted trade openness to foreign products and services in the domestic market (Bista, 2016). In the period 1960-1980s, import trade was restricted from tariff and non-tariff barriers (higher tariff, quota and high subsidy) to protect the domestic industries and to generate revenue resources for development and regular expenditure in the narrow tax base and lower tax elasticity and buoyancy. Its side effect was macro-economic crisis with 5 percent current account deficit, 10.7 percent budget deficit and 13 percent inflation in 1980s (Bista, 2016). Nepal had a question of stability and growth. The World Bank and IMF had recommended Structural Adjustment Program (SAP) to liberalize Nepalese economy. As a result, trade liberalization policy would be executed at some extent. Its full-fledged liberalization was implemented in the 1990s after the effective of SAP II. As follow up, SAPTA-SAFTA was signed in 1993 for regionalism. It was supplemented by Gujural Doctrine in 1996 with unilateral preferential concession to neighbor countries in trade. Its reflection in trade policy, regime and philosophy can be found till date. In recent years, it is curiosity whether trade liberalization 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 unexpectedly heavy load in such the growth of trade deficit.
Since lockdown policy as a powerful anti COVID19 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 to all economic sectors but trade sector was considered unexpectedly extremely broken. By and large, deduction of the external sector in the four sector economies had made all economies closed and isolated economies with undesired and unplanned for short run. It was looked like what classical economist mentioned self-sufficient economies in ancient and medieval period. Thus, trade sector was fully and partially halted in the world.
Nepal has endorsed anti COVID19 measures: hard and soft. In hard measure, strict lock down measure was executed from March 23 to July 21, 2020 to reduce inflow of COVID19 along with human mobility and goods flow. The Indo Nepal and Sino Nepal border and transport were closed down for two months long. Then after, the lockdown was internally removed with restriction but both border’s closed down statuses were obvious. Again, lockdown was formally announced by the government of Nepal from August 16 to Sept 7, 2020, when the government found the higher penetration growth per day of COVID19 in Kathmandu Valley. On Sept 7, it was lifted. As a soft measure, there were effective: 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 the COVID19 will have severed impacts on trade sectors. There were assumptions as follows: a) the lockdown would stop transportation system within the country and Indo Nepal and Sino Nepal trade transit; b) the flow of goods and services in import and export would be stopped; c) the export import ratio in Indo Nepal and Sino Nepal would decline; d) the growth of trade deficit pressure would be unexpectedly lower; f) the capital account would be positive and plus and g) macroeconomic stability would be improved as expected and h) agriculture productivity and production would be better. Therefore, this study is relevant to test above assumptions.
The study would examine mainly two issues: whether the impact of COVID pandemic shock and anti COVID policy measures on the trade of Nepal will be wider and whether the compensatory policy tools to survival stabilize and stimulate the slowdown trade sector will be positive. Its output would be valuable to understand COVID19, Anti COVID Policy and Trade sector relationship and explore compensatory policy to trade sector. It would be valuable literatures to academicians and policy makers to discourse seriously and sensitively on trade sector to reshape and remake it exogenous crisis resilience and survival.
OBJECTIVES AND METHODS
Objectives
The paper examines the impact of COVID pandemic and anti COVID policy on the trade of Nepal. Its specific objectives are a) to assess the impact of COVID pandemic on the trade of Nepal, b) to examine the effect of anti COVID policy measures on the trade of Nepal and c) to find out the compensatory policy tools to survival, stabilize and stimulate the slowdown trade sector.
Data and Methods
Let’s suppose GDP is “Y” and COVID19 positive cases. Let’s assume COVID19 positive cases and anti COVID policy makes slow down to GDP growth. Let’s expand in the regression model as follows
Yit=α+βXit+β1 Dit + ε………. (i)
Where, α= intercept, β=coefficient of COVID19 positive cases (Xit), β1=coefficient of Lockdown and border closure (Xit), ε=error term, Xit=COVID19 positive cases, Xit = Lockdown and border closure,
Where, α, β, &β1 are parameters and have α>1, 0< β1<1 and 0< β2<1.
This paper used secondary data sets of COVID19. It includes COVID positive cases and lock down 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, and National Planning Commission, Nepal Rastriya Bank and Central Bureau of Statistics.
Analytical tool was SPSS to operate simple regression to estimate coefficient.
RESULTS AND DISCUSSION
Result I: COVID Scenario
COVID in the World

Since its outbreak with 44 COVID19’s positive cases in Wuhan City of China in January 9, 2020 (WHO, 2020) but its first report on 31st December, 2019 from Wuhan, China (Isaifan, 2020; Dutheil et al., 2020 and Han et al., 2020), till date, the COVID19 has badly captured more than 210 countries across the World with the result of 5.2million population positive cases, 0.4 million death and more than 0.2 million recovered (WHO, 2020). Horizontally and vertically, it badly smashed the public health system of the World with disclosing its advance technology, services supply and delivered and its standard, along with insufficient beds, testing kits and medicines (Huang et al., 2020, Kambalagere, 2020, Sohrabi et al., 2020 and Zhang et al., 2020). In USA, the overcrowded COVID 19 positive cases could not get bed in the hospitals. A large number of patients were waiting hospital beds and treatments. Similar constraints were found in Italy, Spain, UK, France, Germany etc. (WHO, 2020). In addition, it has induced humanitarian, cultural and religion crisis. Christian community followed firing the death body instead of burying. Social distancing was maintained in the funeral ceremony. In Spain, the over flooded death bodies raised demand of coffin and other. In Guatemala, death body was left a long week in the street (WHO, 2020). Mass death bodies were buried in New York. Thus, COVID19 has been the undesired threat to the health of the population in the World.

Figure 1 & 2 shows the higher growth of its density and gravity in developed countries from June, 2020 to September, 2020. Its example was USA, Spain, Italy, France, Germany and UK in June, 2020.

In September, 2020, USA, India and Brazil, Russia, Spain, France and UK led in the COVID fact sheet. Over a time, its growth was faster than our expectation. Therefore, IMF and the World Bank (2020) projected 3 trillion USD loss and recession as its cost with the growth of more than 50 percent unemployed populations and the growth of more than 50 percent 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 with second rank of India. Figure 4 shows all countries in the COVID pandemic exposure and vulnerable. However, India, Pakistan, Bangladesh, Afghanistan and Nepal were in the risk but Sri Lanka, Maldives and Bhutan were in the controlled situation.

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 19, although there was a gossiping that Nepal was a COVID resilient country when COVID cases were sluggish and negligible from March 23 to July 21, 2020. Figure 5 shows its fast growth from May 25, 2020 when labor migrants started to return from India, China, Saudi Arab, Malaysia, etc (WHO, 2020). Then after, its trend was looks like rocketing with geometric growth. In Sept 2020, it reached 77817, 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 at lock down I and II but 80 percent recovery rate made comfortable in that COVID crisis.

Result II: COVID pandemic and Trade
COVID pandemic had direct and indirect effects. In addition, the effective of strict lock down and border shield as anti COVID measures was expected its negative outcomes at macro and micro economic level including economic growth, employment, sector output and performance, trade and balance of payment (BOP), fiscal deficit, livelihood, poverty etc. Figure 7 shows contraction of transport and communication by -13.25 percent and then -7.16 percent contraction of trade in the comparison with the pre COVID scenario (MOF, 2020). It was followed by hotel/restaurant, government service and industry. Thus, overall economy was slow down.

Figure 8 shows the huge contraction of import and export trade with India and China from the pre COVID scenario. In the pre COVID, export and import ratio was 1:14 in Indo Nepal trade and 1: 44 in Sino Nepal trade. In the post COVID, its ratio sharply felt down 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 Rs from 1161.2 billion Rs. In Sino Nepal trade, it felt with 40 billion Rs meanwhile in Indo Nepal trade, it was 100 billion Rs. Despite its negative implication on sector and aggregate economy, its positive implication was the soften trade deficit pressure to current account and capital account and then Balance of Payment. Similarly, other SAARC countries, Nepal got positive Balance of Payment leading to improving macroeconomic stability but negative economic growth (Figure 10).



Besides it, there were the observations and facts as follows:
- A big threat- open border induced unauthorized and informal indo Nepal trade was sharply falling down during the Indo Nepal border Shield and closure of transportation and communication.
- Black markets and smuggling markets were temporarily closed down but its benefit could not be seen in formal trade, custom revenue and fair market competition.
- Crime rate related unauthorized and informal trade felt down in Indo Nepal border markets and settlements.
Result III: The impact of Anti COVID measure on Economy and Trade
Table 1 presents descriptive statistics (mean and standard deviation). In column 1, three variables are GDP(Y) as dependent variable and COVID19 (x) and Lockdown & border closure (D) measures as independent variables. Standard deviations of these variables are no so far significant from mean, except lockdown and border closure.
Variable | Mean (Standard Deviation) |
GDP (Y) | 3.4906E3(175.20) |
COVID19 (x) | 98.2727 (101.48) |
Lockdown & border closure (D1) | 2.9765E2(162.26) |
Table 2 presents the results of simple multiple regression model in which dependent variable is GDP(Y) and two independent variables are COVID19(X) and lockdown and border closure (D) having two parameters: β and β1 . In the results of the regression model, parameter (β) explains marginal change of COVID19 cases (x) i.e. change in GDP and change in COVID19 cases ratio. In other words, change COVID19 explains to change 1 percent of GDP. Similarly, parameter (β1) explains whether 1 percent change in GDP will be in lockdown and border closure or not.
Dependent variable: Average Real GDP(Y) | |||
Regressor | 1 | 2 | 3 |
Constant | 3787.3 (4.5) | ||
COVID19 (X) | -0.407(0.033) | ||
Lockdown & Border closure (D) | -0.86(0.021) | ||
Observations | 44 | ||
Overall R2 | 0.99 | ||
Note: * is <5 percent of P value. Dependent variable: GDP |
Considering above results of the econometric model, they provide sufficient evidence on share of independent variables: COVID19 (x) and lockdown and border closure (D) in GDP. In order to minimize the undesired threat of COVID19 pandemic and its fast transmission rate, national economy i.e. real GDP(Y) was directly and indirectly derailed by the COVID19 pandemic and Anti COVID19 policy measures. In the model, p-value of these two independent variables shows significant and valid. Parameter (β) of COVID19 shows a negative sign with 0.44 values and parameter (β1) of lock down and border closure shows negative sign 0.86. In the result of the model, R2 is 0.99. It explains dependent variable GDP(Y) by 99 percent from independent variables: COVID19 (x) and lockdown and border closure (D).
Above results shows both independent variables: COVID19 (x) and lockdown and border closure (D) having negative relationship with GDP. It means COVID19 having negative impact on GDP and Anti COVID Policy has also the side effect of contraction shock to GDP by making zero trade openness and zero mobility of goods and services flow. The level of negative impact of anti COVID19 policy: lockdown and border closure is more than COVID19. It is anti COVID19 policy has negatively contributed 0.86 percent to 1 percent marginal change of GDP but COVID19 j has only 0.44 percent to 1 percent marginal change of GDP. Therefore, anti COVID policy was disastrous to the trade of Nepal.
Result IV: COVID pandemic, Trade and Compensatory Policy Measures
In above empirical results, COVID pandemic and anti COVID policy were significantly negative to GDP or sector economy of Nepal, particularly trade sector by zero trade openness and zero goods and services flows over 7 months (March to September, 2020). ADB (2020), IMF (2020) and World Bank (2020) projected its side effect as contraction with 3 percent negative economic growth towards economic recession. During the COVID19 pandemic, the economy had a big pressure of stabilizing COVID19 pandemic growth and stimulating 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: a) compensating to the poor and marginal people in public utility, b) rescheduling tax payment to trade, business and industries, c) compensating to small and micro enterprises with tax cut, d) proposal for Stimulus Package to Business sector: i) allocation of 6 billion Rs on medicine supply and management, ii) Compensation to the poor and marginal people by free electricity to 10 units electricity consumer groups, 25 % exemption to upto 150 unit electricity consumer groups, 50 % exemption to upto 250 unit electricity consumer groups, Free Water bill, 100 billion Rs. Fund for Tourism Sector’s rehabilitation and recovery, 100000 insurance to all health workers, Full exemption to Airlines on their rent, Exemption of Renewal charge to communication and film industry and 50 billion Rs. Fund for new innovative projects and programs, e) tax exemption to comparative advantage able export items, f) expanding Integrated Custom office in all custom points, g) development and operation of dry ports in Indo Nepal and China Nepal border, h) review Indo Nepal and Nepal China Trade and Transit Treaty, i) exemption of Income tax on Small and Micro Enterprises for seven years -75% income tax exemption to < 2 million investment, 50 % income tax exemption to 2-5 million investment, 25% income tax exemption to 5-10 million investment, j) removing VAT on micro insurance, k) reducing custom duties on the import of agricultural products, l) 20 percent income tax exemption to tourism transport, m) Custom duties exemption to Medicinal and homeopathy medicine and n) 50 % income tax exemption to internet service.
Policy Shock III: Monetary Policy 2020-2021 was disclosed by the Central Bank of Nepal, Nepal Rastriya Bank (NRB, 2020). The policy carries the compensatory policy as follows: a) compensatory through Rehabilitation, Recovery and Rescheduling Fund, b) rescheduling credit’s principal and interest payment, c) refinancing to the vulnerable enterprises and industries through the Fund, d) special interest rate to the vulnerable enterprises and industries, e) lower interest rate to the small and micro enterprises, f) management to liquidity, g) merging banks and financial institutions, h) establishing Hedging fund, i) 15 percent Credit on priority sector – agriculture, energy, tourism and small and micro enterprise, j) facilitate credit to agricultural projects and small and micro enterprises at 5 percent interest rate, k) five times refinancing to the available refinancing fund, l) credit at 3 percent to export oriented and vulnerable industries and enterprises, m) credit at 5 percent to small and micro enterprises and n) establishing 50 billion NRs for credit rescheduling and refinancing.
Despite the compensatory policy, there would be issues as follows: a) no execution of above these 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.
CONCLUSION
This paper analyzes the impact of COVID19, anti COVID policy and compensatory policy on trade of Nepal based on secondary data through descriptive statistics and regression model tools. As a result, COVID19 infected to 44.8 million populations and killed 1.2 million people of 215 countries of the World, where its extreme intensity felt on USA and G20 countries and on India in South Asia and Brazil in South America. Subsequently, its economic consequence is a loss of 3.4 % economic growth rate, worst stock market crash, loss of 400 million full time job and US$ 3.5 trillion GDP loss (IMF, 2020 & UN, 2020). Similarly, in SAARC, Nepal ranks at fourth jumping at 35th of 215 countries of the World with 0.165 million affected people, 887 death toll, per day new cases >3000 and recovery rate >74 percent. Furthermore, the empirical result is the negative impact of COVID19 and anti COVID policy to national economy, particularly trade. Anti COVID policy’s impact (0.86) is more severe than COVID19 (0.44) in the economy. Its output is most vulnerability to trade: Indo Nepal and Sino Nepal. Its outcomes are mixed: negative to sector economy, employment and economic growth and positive to trade deficit, trade dependency and balance of payment. The compensatory policy is a stable shock to the negative consequence of COVID19 and anti COVID policy. Therefore, Nepal is a vulnerable to COVID19 and trade sector is most vulnerable. For survival, stable and stimulus of 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 organized 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’
YouTube Video for ‘Trade and Policy Shocks in Nepal amid the COVID-19 Pandemic: Observations, Lessons and the Way Forward‘
Read more on the event here.