Annual GDP Research Articles

The involvement of Non-Governmental Organizations activities in Household Poverty reduction in Oyam District, Uganda

Purpose: This study examined the contribution of NGO activities on poverty reduction in Oyam District-Northern Uganda and recommends strategies for improving wellbeing of people of the region and entirely Uganda as a Country. This was based on account that, Oyam District was estimated with the lowest annual GDP per capita of 223 USD compared to the neighbouring Districts of Apac and Kole with the annual GDP per capita of 228 USD and 230 USD respectively
 Methodology: The study used a correlational design with correlational and regression methods of analysis. It was conducted among beneficiaries of selected NGOs comprising a sample of 290 from a population of 860.
 Findings: This study reveals a significant and positive contribution of NGO activities to poverty reduction in Oyam District and that NGO activities has a moderate relationship with household poverty level in Oyam District. The results further show that the financial support provided by NGOs significantly contributes to poverty reduction while the food security support provided does not.
 Conclusion and recommendations: It is established that NGO activities contribute significantly to poverty reduction in Oyam District. This study recommends that the food security support be backed with the provision of market for the agricultural products of the NGO beneficiaries and in order to create income for them. The study further recommends for the NGO support to agricultural product market search for their beneficiaries as well as forming the beneficiaries in different groups and train them on financial literacy for better management of finances.
 Unique contributions to policy and/or practice: This study contributes positively to the understanding of non-state actors and the role they play in reducing poverty among communities that are recovering from decades of civil war in Uganda.

The spillover effects of rising energy prices following 2022 Russian invasion of Ukraine

This study examines how the rise in energy prices following the Russian invasion of Ukraine (which began on February 24, 2022) has spread to other sectors using the monthly input–output model (56 sectors in 44 countries). The estimated results demonstrate that if prices increase by 20% exclusively in Russia’s mining and quarrying (M&Q) sector, there will be almost no global effect. However, if prices increase by 20% in every M&Q sector around the world, global prices (the weighted average across all sectors) will rise by 3.15%, damaging 6.83% of monthly GDP at the pre-invasion level as a surplus loss ($551,080 million per month). Because oil prices rose for almost five months from February 28 to August 3, 2022, the world suffered five times this damage, or 2.85% of annual GDP ($2.7 trillion). This scenario is roughly equivalent to a price change of 5 times in the Russian M&Q sector alone.

Prediction of Spatiotemporal Changes in Sloping Cropland in the Middle Reaches of the Yangtze River Region under Different Scenarios.

With the rapid urban expansion and extensive occupation of cropland, sloping cropland has become an important cropland resource across China. How sloping cropland will change under different socioeconomic scenarios is poorly understood. Therefore, we modeled land-cover change using SSP-RCP multi-scenario simulations and analyzed the evolution and driving factors of sloping cropland change in the middle reaches of the Yangtze River Region (MRYRR). The results indicate the following: In the past twenty years, the cropland and sloping cropland areas in this region declined but the proportion of sloping cropland in total area has been increasing. The average slope of sloping cropland has increased from 7.95° to 8.28°. By 2035, the sloping cropland and total cropland areas will continue to decrease according to the current trend (SSP2-4.5). The average slope will increase maximally to 8.63° under the SSP4-3.4 scenario and minimally to 8.45° under the SSP4-6.0 scenario. Under SSP4-3.4, the extent of slope increase will exceed that in 2005-2010, when regional cropland slope showed the strongest increase in the past. Among 14 social, economic, and ecological factors, average annual precipitation and GDP contributed the most to the change in sloping cropland. This study provides support for decision-making in sustainable land resource allocation to balance urban expansion and cropland conservation.

Determinants of working capital management of firms in selected industries in Croatia

Considering the theoretical findings and the empirically determined relevance of working capital management (WCM), the paper focuses on identifying the WCM determinants of manufacturing, trade, and information and communication companies in Croatia. The time horizon of the analysis ranges from the year 2008 to the year 2015, and the final sample consists of 19,355 companies or 116,002 firm-year observations. In addition to the methods of descriptive statistics, the Kruskal-Wallis test, Dunn’s post hoc test, and panel regression analysis are used as methods of inferential statistics. The results of identifying the determinants of WCM indicate that WCM in the previous year, profitability, and financial constraints significantly positively impact working capital cycles, thus promoting conservative WCM. In contrast, size, growth, fixed investment, annual real GDP growth, and industry indicators were significantly negative predictors of the two WCM indicators used, the cash conversion cycle (CCC) and the net trade cycle (NTC). Accordingly, the latter stimulates aggressive WCM. Given the significantly positive effect of an aggressive WCM strategy on profitability, together with the results of the test of WCM determinants, it is recommended that the firms studied to use these determinants to generally manage net operating working capital in a narrower sense more aggressively and achieve its target values.

Trade, GDP value adding activities and income inequality in the East African community

This paper investigates the extent to which the East African Community (EAC) countries have developed economically over time and whether income inequality decreases with economic growth. The relationship between trade and GDP per capita amongst EAC member countries is evaluated using the World Bank’s meta-data of development indicators and the EAC Secretariat’s data spanning from 2000–2019. Convergence in GDP per capita and inequality are tested using Coefficient of variation (CV) and weightedbeta. The results show that agriculture, manufacturing, trade and repair, construction, and transport and storage constituted the top five GDP value adding activities, contributing about 38 percent to total annual GDP. The EAC GDP per capita were diverging in the long run but converging in short to medium terms, implying increase and decrease in the regional income inequality respectively. Agriculture, electricity and gas, transport and storage, real estate activities, public administration, and education were income inequality-increasing sectors. Together with finance and insurance, these sectors were also positively associated with GDP per capita. The exports of EAC member countries were found to be highly concentrated in few sectors and destination markets, implying limited diversification of products and markets. In their quest to diversify, these countries should choose the right mixes of export goods and services keeping in view of the prevailing market factors in importing countries, such as, changing taste and demands.

Recessions and recoveries in Central African countries: Lessons from the past

AbstractThe Great Financial Crisis and the COVID‐19 pandemic have raised concerns about business cycles. In this paper, we examine the dynamics of past business cycles in CAEMC economies to infer the shapes of recessions and subsequent recoveries. We use annual GDP data covering the period 1960–2020 and non‐parametric approach. The main results are fourfold. First, recessions are, on average, long with a positive duration dependence relationship and the strength of recoveries is independent of the duration and the depth of the associated recessions. Second, recessions and recoveries are not all alike, meaning that history cannot be used as a guide for forecasting issue. Third, nearly 45% of the recessions and subsequent recoveries are V‐shaped, and the L, U and W patterns appear when governments are heavily indebted. Fourth, a regional cycle sometimes emerges. The results suggest a strengthening of the capacities of CAEMC states and a resilient supply chain management.

The Boundary of Porter Hypothesis: The Energy and Economic Impact of China’s Carbon Neutrality Target in 2060

The process of carbon neutrality does have economic costs; however, few studies have measured the cost and the economic neutral opportunities. This paper uses a dynamic computable general equilibrium (CGE) model to simulate China’s carbon neutrality path from 2020 to 2060 and analyzes its economic impact. This paper innovatively adjusts the CGE modeling technology and simulates the boundary of the Porter hypothesis on the premise of economic neutrality. The results show that the carbon neutrality target may reduce the annual GDP growth rate by about 0.8% in 2020–2060. To make the carbon pricing method under the carbon neutrality framework meet the strong version of the Porter hypothesis (or economic neutrality), China must increase its annual total factor productivity by 0.56–0.57% in 2020–2060; this is hard to achieve. In addition, the study finds that China’s 2030 carbon target has little impact on the economy, but the achievement of the 2060 carbon neutrality target will have a significant effect. Therefore, the paper believes that the key to carbon neutrality lies in the coexistence of technological innovation and carbon pricing to ensure that we can cope with global warming with the lowest cost and resistance.

The Padma Multipurpose Bridge: A Link towards a Prosperous Future through Connectivity and Mobility

This study describes the impact of the Padma Multipurpose Bridge in creating regional connectivity and mobility in traffic movement, thus contributing to the socioeconomic development of Bangladesh. It finds that the travel time between the Dhaka division and the southwestern region will be saved by about two hours for cars and buses and by over 10 hours for trucks due to new connectivity through the bridge. It will reduce the distance from Mongla Port to Dhaka by more than 100 km to 170 km and save a lot of working hours, which will further accelerate the growth of the country’s economy. Additionally, a total of 212.05 km of the new railway line is being constructed for the Padma Multipurpose Bridge, which will connect Dhaka with the country’s largest land port, Jessore. After the Padma Bridge Rail Link project is done, the travel time from Dhaka to Kolkata via Jessore will be cut in half, and it will take only 3 to 4 hours. Moreover, the bridge will also pave the way for putting in place a new route for the Trans-Asian Railway network. The Padma Multipurpose Bridge is estimated to boost the country’s annual GDP by 1.23 percent and the southwestern region’s GDP by 2.5 percent. Moreover, the Padma Multipurpose Bridge will reduce the poverty rate by 1.01 percent at the regional level and by 0.84 percent at the national level. This study finds that to take full advantage of the newly constructed bridge, the southern part of the outer ring road of Dhaka proposed in RSTP should be completed soon. Padma Multipurpose Bridge will work as a key component of Asian Highway-1, boosting economic growth in Asia and improving the country's standing on the continent.

Banking regulation and banking crises Probability in european countries

The main hypothesis of the paper was the thesis that banking regulation is intended to minimize the probability of financial instability, including banking crises, which have long-lasting and destructive consequences for the economy.The practical aim of this investigation is to explore the impact of banking regulation instruments on the banking crisis probability. Despite a large and growing body of literature that has investigated the role of banking regulation in ensuring financial stability, only a few of them explored the aspect of this problem we are considering, and this constitutes the scientific novelty of the research.The results confirm the effectiveness of banking regulation in predicting periods of stability in banking systems.Based on the use of bibliometric analysis with the software tool VOSviewer v.1.6.10, the main patterns in the theory of banking regulation development have been identified. To conduct an empirical analysis, the author used a database of eleven European countries from 1998 to 2017, whose banking systems had manifestations of a systemic banking crisis. Binary modeling (logit model) was used as a scientific and methodological tool for statistical research. The conducted empirical analysis declared the need to tighten banking regulations in the field of non-performing loan control since it leads to an increase in the banking crisis probability. The results of binary modeling also emphasized the importance of macroeconomic and monetary factors, the neglect of which leads to the vulnerability of banking institutions and, consequently, to banking crises.An important conclusion of the analysis is that in order to minimize systemic banking crises, it is necessary to ensure the achievement of the target parameters of the main macroeconomic indicators, expressed in terms of the optimal level of inflation and annual GDP growth. The proposed binary model can be used to further study the causes of a banking crisis, as well as methodological and empirical clarification of the role of banking regulation in the probability of its occurrence.

Investigation of the relationship between the dynamics of GDP and economic sentiment index

The paper develops and presents an appropriate model toolkit that allows assessing the relationship between the calculated indices of economic sentiment and confidence for the main types of economic activity. The aim of the study is to experimentally substantiate the relevance of data on the opinions of technological economic agents and assess the value of this information for the statistical description and analysis of macroeconomic trends, including economic cycles and unforeseen and prolonged crises. The main hypothesis about the cyclical sensitivity of composite indices, in particular the index of economic sentiment in relation to the dynamics of the physical volume of GDP, is tested. The authors calculate a composite indicator of aggregate economic sentiment and, based on a consistent analysis of the relationship between the index of physical volume of GDP and the indicator of economic sentiment, identify aggregate empirical patterns and features of the cyclical development of technological enterprises. Accordingly, the turning points of the business cycle are discussed and the leading nature of the proposed index of economic sentiment is affirmed. The importance of the composite indicators in the economic analysis of entrepreneurial behavior in the implementation of technological innovations is shown. The nature of the calculated Economic Sentiment Index was established, and its predictive capabilities for monthly and annual real GDP growth rates using autoregression and error correction models were investigated. The stages of calculating and setting indices with the application of the DEMETRA+ statistical package were implemented.

Population, biomass, and economic value of small ruminants in Ethiopia.

Ethiopia has a large population of small ruminants (sheep and goats) which are mostly kept in traditional subsistence production systems that are poorly described. Understanding these different systems, their population structure, biomass, production, and economic value is essential for further analysis and effective policy making. The objective of this study was to quantify these parameters for small ruminant production systems in Ethiopia to use them as a basis for analysis of disease burden within the Global Burden of Animal Diseases program. Population structure and trends of small ruminants were analyzed using data from ten annual national agriculture surveys. A stochastic herd model was used to simulate the small ruminant population, biomass, and economic value. The model was parameterised stochastically using data from statistical databases and the literature, and sensitivity analysis of main model outputs to the stochastic inputs was done. Small ruminants are held across the country mainly managed under two major production systems: the crop-livestock mixed system and the pastoral system. The small ruminant population has grown in the past 10 years with an average annual growth rate of 4.6% for sheep and 6.7% for goats. The national average small ruminant population for 2021 was projected at 96.4 (range 95.3–97.7) million heads and the mean stock biomass was about 2,129 (range 1,680–2,686) million kilograms. The monetary value of the small ruminant population was estimated at USD 5,953 (range 4,369–7,765) million. The annual monetary value of small ruminant production outputs was estimated at USD 1,969 (range 1,245–2,857) million. Although the small ruminant population is large and rapidly growing, contributing about 2% of national annual GDP, the sub-sector is characterized by low productivity, low offtake rates, and a limited range of production outputs with no signs of intensification. Efforts should be made to reduce small ruminant mortality, improve fertility, and better utilize products such as milk to improve the livelihoods of rural households and to benefit the national economy. The approaches developed in this study can be replicated in other systems and countries to reveal trends in the size and value of livestock systems, providing a better understanding of its economic importance and performance.

The The Effects of Annual GDP growth on Consumption Spending: Evidence from West African Countries

This study examines the effect of annual growth in gross domestic product on consumption spending in the West African Countries from the period 2005 to 2020. Consumption has been a fundamental driver of economic growth, and the insufficient consumption spending will lure firms to lay off workers which can lead to short run fluctuation in the economy. The study employed a dynamic panel model with a set of estimation strategies such as fixed and random effect, Anderson and Hsiao (1982) estimation, difference and System-Generalized Methods of Moment and Least Square Dummy Variable estimation methods to correctly assess how annual GDP growth affect consumption spending in these countries including additional variables such as, Lag consumption spending, foreign direct investment, consumer prices as a measure of inflation and a vector of control such as capital formation and annual population growth. The study found that annual GDP growth and Foreign direct investment has a significant impact on increasing consumption spending thus annual GDP growth is the most crucial factor for increasing consumption spending in these countries. Moreover, lagged consumption spending is also found to have a negative significantly effect in reducing current consumption spending while gross capital formation and annual population growth are found to have an insignificant effect in reducing consumption spending in all the estimates except in the Anderson and Hsiao (1982) estimation method which shows a positive relationship with consumption spending.

CONSUMER CONFIDENCE AND REAL ECONOMIC GROWTH IN THE EUROZONE

Over the past 15 years, the world economic system has experienced two global crises: the financial and economic crisis of 2008 and the pandemic crisis of 2020. The financial crisis of 2008 had a significant impact on the development of the world economy, including the eurozone. Although some sectors of the economy are not recovering and have not reached pre-crisis levels of efficiency, overall economies are characterized by predictable and positive economic trends. The pandemic crisis poses new challenges to the economy in terms of business closures, disrupted supply chains, and high and accelerating inflation. All this brought to the fore the need to analyze the correlations between various indicators and the dynamics of economic growth, so that when unforeseen crises occur, decisions can be made quickly. The aim of the study is to analyze the degree of correlation between the indicator of consumer confidence and real GDP growth by quarter in the euro area. The tested hypothesis is that for the last three years there has been a strong correlation between quarterly data on real economic growth and consumers' direct assessments, as expressed by the consumer confidence indicator. The regression analysis and hypothesis testing are performed using seasonally adjusted monthly data on consumer confidence indicator and seasonally adjusted annual data by quarters on real annual GDP growth in Q2 2019 – Q1 2022. The in-depth regression analysis shows that there is a statistically significant linear relationship between the indicator of consumer confidence and real annual GDP growth by quarters for the period under study. The results of the Granger causality test confirm the conclusions drawn from the dynamic, correlation, and regression analyses. The results of the test prove not only the presence of causality, but also the ability of the consumer confidence indicator to predict real annual growth by quarter during periods of crisis. All this allows to conclude that in periods of import crises, the indicator of consumer confidence can also be used as an early signal of the presence of systemic problems and to determine the dynamics of GDP, as well as to implement specific economic measures and policies.

Measuring the Connotations of Economic Variables with External Debts of Bangladesh

This study ascertains the associations of the macroeconomic variables with external debts, the impacts of external debts on annual GDP, GDP growth, and per capita income, and the timing effects on the economic variables of Bangladesh. The analysis is inferential and eight hypotheses have been set and tested with the regression analysis. To complete the study, the chi-squared test and Durbin-Watson test have been used along with trends and growth analysis. The results of the study reveal that the budget deficit, current account deficit, and defense budget have a positive association with external debts. Furthermore, foreign direct investment, foreign exchange reserve, foreign remittance, and trade of balance have a negative association with external debts. The external debts have no negative impact on annual GDP, GDP growth, and per capita income. Finally, there is a significant timing effect on the economic variables of Bangladesh during the study period.

The Temporal–Spatial Characteristics of Column NO2 Concentration and Influence Factors in Xinjiang of Northwestern Arid Region in China

This paper investigates the temporal–spatial characteristics of column NO2 concentration and influence factors in Xinjiang based on the Tropospheric Monitoring Instrument (TROPOMI) aboard the EU/ESA Sentinel-5 Precursor satellite. The findings indicate that there is a high linear correlation between TROPOMI NO2 data and ground-based data, with Yining having the highest correlation (R2 = 0.8132) and Aksu having the lowest correlation (R2 = 0.7307). The TROPOMI NO2 data can be used to approximate the characteristics of near-surface atmospheric NO2 concentration. NO2 VCD in the troposphere varies greatly geographically, with a noticeable ‘island’ pattern. The high-value zones are mostly found on the northern slope of Tianshan Mountain, in the capital cities of several prefectures, and occasionally in the industrial parks. Urumqi has the highest annual average NO2 VCD of 553.9 × 10−6 mol·m−2. The NO2 VCD is characterized by seasonal shifts and cyclical swings of “low in spring, high in winter, and transition in summer and autumn”. The monthly mean value is highest in December (27.14 × 10−6 mol m−2) and lowest in March (12.66 × 10−6 mol m−2). Meteorological factors can influence the temporal and spatial distribution of NO2 VCD. The GRA in Urumqi is 0.774 between the monthly mean of NO2 VCD and relative humidity. The main causes of the increase in NO2 VCD are man-made emissions. The annual GDP of the secondary industry and its annual average NO2 VCD in fifteen key cities in Xinjiang have a correlation coefficient of 0.78. TROPOMI NO2 data can provide strong support for the fine control of air pollution and air quality in early warning forecast in Xinjiang.

LEVERAGING CPFTA FOR NATIONAL ECONOMIC GROWTH AMIDST GLOBAL CRISES

The global challenges related to pandemics and political disputes are one of the hardest front confronted by international development cooperation and becomes the challenge for regional integration initiatives. During the phase of pandemic it is the matter of great concern for all the governments not only to identify possible outcomes to minimize long term losses to their economies but to facilitate the residents for their recovery to challenge the issues of maintaining their livelihood, poverty, employment and through provision of global public goods.The impact of Trade agreements is long-term on a country's economic outlook. China-Pakistan FTA-I entered into force w.e.f Oct.10th, 2009 and bring zero rates on 35.5% of tariff lines and the CPFTAII entered into force w.e.f. Jan-2020 and in terms of tariff lines, China liberalized 1026 new tariff lines. Under CPFTA, China’s tariff on 313- priority tariff lines were eliminated that which cap over $8.7 billion worth of our International exports and over $64 billion worth of imports from China. As a result, though trade with China has increased manifold, still it could not achieve desired results. Additionally, domestic and global economies are passing through an extraordinary time when the world is confronted by pandemic uncertainties and economic threats convoluted by the Ukraine war crunch, where national preferences shaping against globalization. In this background, we need to fast find solutions to these issues and explore how bilateral agreements can be leveraged for enhancing trade ties for sustainable economic growth. This study examines the trade response using export and import data, which indicates the intensity of trade reciprocity by analyzing pre, and post-CPFTA conditions. This study, therefore, aims to comprehend the role of the China-Pakistan Free Trade Agreement (CPFTA) in Pakistan’s trade regime and its contribution to the economy. The study has compared the imports and Pakistani exports to China during and after the CPFTA-I based on Pakistan’s annual GDP growth rate while for due short period of time from 2019 onwards CPFTA-II data is not utilized for analysis. The resulting analysis will be used to recommend measures to increase trade with China and other regional countries, address non-tariff impediments to maximize utilization of the FTA, and address bottlenecks for the implementation of the Free trade agreement and the results foreshadow forthcoming mutual trade in fields of technology, investment, Agriculture, Blue growth and CPEC between both nations.

Transformation of international migrants in head wind: Evidence from Tajikistan in the 2010s

AbstractTajikistan has relied on remittances by international migrants that have exceeded a quarter of annual GDP to date, despite a series of exogenous adverse events in the mid‐2010s. We use a nationally representative panel dataset collected in 2013 and 2018 to explore the socio‐economic characteristics of households with international migrants and migrants themselves. We provide several new findings. First, the prevalence of households with international migrants is 40%, with a substantial transition in migrant status during the research period. Second, households with international migrants are not poor, have Russian‐speaking members, and are supported by an intense migration network. Third, younger, single, and more educated males comprise most of Tajikistan's international migrants. Fourth, households without Russian‐speaking members or migration networks in 2013 had begun to send international migrants by 2018, while households in the richest group had exited from migration, suggesting s transition of the socio‐economic composition of migrant‐sending households during the mid‐2010s.

The Export of Medium and High-Tech Products Manufactured in Europe

In this article we analyze the determinants and the export trend of European countries of medium and high technology products. The data were analyzed using various econometric models, namely WLS, Pooled OLS, Dynamic Panel, Panel Data with Fixed Effects, Panel Data with Random Effects. The results show that exports of medium and high-tech products are positively associated, among other variables, with the value of “Average Annual GDP Growth”, “Total Entrepreneurial Activity” and “Sales Impacts”, and negatively associated with, among other variables, “Human Resources”, “Government and Procurement of Advanced Technology Products” and “Buyer Sophistication”. A cluster analysis was realized with the k-Means algorithm optimized with the Silhouette coefficient. The result showed the presence of only two clusters. Since this result was considered poorly representative of the industrial complexity of the European Union countries, a further analysis was carried out with the Elbow method. The result showed the presence of 6 clusters with the dominance of Germany and the economies connected to the German economy. In addition, a network analysis was carried out using the distance to Manhattan. Four complex network structures and two simplified network structures were detected. A comparison was then made between 10 machine learning algorithms for predicting the value of exports of medium and high-tech products. The result shows that the best performing algorithm is the SGD. An analysis with Augmented Data-AD was implemented with a comparison between 10 machine learning algorithms for prediction and the result shows that the Linear Regression algorithm is the best predictor. The prediction with the Augmented Data-AD allows to reduce the MAE by about 0.0022131 compared to the prediction with the Original Data-OD.

An ocean apart? The effects of US business cycles on Chinese business cycles

This study investigates the economic interdependence between China and the United States. In view of the growing trade and investment between China and the United States, and the reaction of the Chinese economy to the US subprime mortgage crisis, one might reasonably ask, what effect do US business cycles have upon the Chinese economy? We approach this problem by examining various channels of economic interaction, including international trade and foreign direct investment between the two countries. We use regressions, the Markov switching vector autoregressive model, and recursive correlations in an attempt to measure business cycle transmission from the United States to China using annual, quarterly, and monthly data.With both annual and quarterly GDP growth data between 1951 and 2001, business cycles in China and the US are not correlated. Starting in 1978, China undertook significant economic reforms and opened up to the rest of the world. After 1992, trade between the US and China increased, and US firms began to engage in FDI in China. After China's accession to the WTO in 2001, trade accelerated, and the correlation between the GDP growth rates of the US and China increased dramatically. There is evidence that the US has some marginally significant but increasing business cycle transmission effects upon China. Recursive correlations reveal that the synchronization between the two countries is strongest during economic downturns, suggesting that economic downturns and crises are responsible for most of the business cycle synchronization.

Reducing the basic reproduction number of COVID-19: a model simulation focused on QALYs, hospitalisation, productivity costs and optimal (soft) lockdown

Even if public health interventions are successful at reducing the spread of COVID-19, there is no guarantee that they will bring net benefits to the society because of the dynamic nature of the pandemic, e.g., the risk of a second outbreak if those interventions are stopped too early, and the costs of a continued lockdown. In this analysis, a discrete-time dynamic model is used to simulate the effect of reducing the effective reproduction number, driven by lockdowns ordered in March 2020 in four European countries (UK, France, Italy and Spain), on QALYs and hospitalisation costs. These benefits are valued in monetary terms (€30,000 per QALY assumed) and compared to productivity costs due to reduced economic activity during the lockdown. An analysis of the optimal duration of lockdown is performed where a net benefit is maximised. The switch to a soft lockdown is analysed and compared to a continued lockdown or no intervention. Results vary for two assumptions about hospital capacity of the health system: (a) under unlimited capacity, average benefit ranges from 8.21 to 14.21% of annual GDP, for UK and Spain, respectively; (b) under limited capacity, average benefits are higher than 30.32% of annual GDP in all countries. The simulation results imply that the benefits of lockdown are not substantial unless continued until vaccination of high-risk groups is complete. It is illustrated that lockdown may not bring net benefits under some scenarios and a soft lockdown will be a more efficient alternative from mid-June 2020 only if the basic reproduction number is maintained low (not necessarily below 1) and productivity costs are sufficiently reduced.