Trade Liberalization and Economic Development Essay Example

having a significant influence on development outcomes. In the past years, there has been a global surge in market-oriented initiatives, resulting in the liberalization of aspects like capital account, foreign exchange, credit, domestic consumption, and trade across various countries.

Trade liberalization, also known as the reduction of obstacles to the movement of goods and services in global trade, has gained significant attention in different economies. Bhagwati and Krueger argue that any policy aiming to minimize antiexport bias contributes to promoting trade liberalization. They further highlight the importance of reducing the import license premium as a critical measure for establishing a regime that supports liberalized trade. Edwards (1993) offers another perspective by defining a liberal trade regime as one that eliminates all distortions in trade, such as import tariffs and export subsidies.

Trade liberalization, as suggested by the new growth theory, has various impacts. It enhances the market and encourages research and development. Furthermore, it results in a shift in employment towards more advanced activities that demand higher human capital levels. Moreover, trade liberalization facilitates knowledge exchange between nations. Nevertheless, there are drawbacks associated with trade liberalization.
One significant disadvantage is the decrease in tariff revenue when trade barriers are reduced due to trade liberalization. In developing countries, this revenue usually represents 10-20 percent of government income.

Lowering or eliminating tariffs will require nations to significantly raise taxes to sustain their budgets, potentially causing economic imbalances. The push for trade liberalization is also expected to disrupt the agricultural industry, as quickly removing restrictions on imported agricultural goods could lead to the mass displacement of rural communities (Edwards, 1993).

The Human Development Report (2003)

states that standard economic models assume that people who lose their jobs due to rapid liberalization will quickly find new employment in other industries. However, this can result in increased levels of unemployment and underemployment, as well as socio-economic instability. Furthermore, it may create an unequal distribution of advantages and disadvantages, with the economy benefiting overall while a particular group bears the majority of the adjustment challenges.

Since the 1970s, trade liberalization has been important in development policies due to significant changes in global economic policies. The World Trade Organization (WTO), established in 1995, has further encouraged trade liberalization. Acting as a platform for nations to resolve trade disputes, the WTO aims to improve transparency and openness in international trade.

In the mid 1960s, East Asian countries implemented an outward development strategy which included import substitution and government control. This shift resulted in improved gross domestic product growth rate, exports, and living standards for these nations. Additionally, it allowed them to sustain their progress despite challenges such as the oil shock of the 1970s and the debt and recession period in the early 1980s.

Behrman and Srinivasan (1995) state that the per capita income of Hong Kong, Korea, Singapore, and Taiwan witnessed significant growth in the 1990s compared to the 1960s. Hong Kong had an annual increase of 6.2% from 1965 to 1990. Similarly, Korea experienced a 7.1% increase, Singapore saw a rise of 6.5%, and Taiwan had an increase of 8.1% during this time period. Many studies have provided ample evidence that trade liberalization plays a crucial role in the development of the global economy, either positively or negatively.

A study by

Greenaway et. al. (2002) investigated the relationship between trade liberalization and GDP growth rate in 73 developing countries. The research focused on non-tariff measures, export incentives in Taiwan since the mid-1950s, and Hong Kong's laissez-faire economy.

Korea implemented an export-focused system in the early 1960s, while Singapore achieved remarkable growth by separating from Malaya in the mid-1960s. Factors such as barriers, average tariff, black market exchange rate premium, the economy's socialist nature, and the existence of state monopoly over key exports influence this. Additionally, the level of quotas, tariffs, export obstacles, and promoters, as well as exchange rate misalignment, play a role. Finally, the presence of a dummy variable for the structural adjustment program and a World Bank (WB) indicator are considered.

The study used the ordinary least squares (OLS) method to analyze three different time periods and indicators in order to obtain empirical results. In the short term, trade liberalization had a positive and significant impact on growth according to two indicators, while one indicator showed no significant impact. Additionally, all indicators indicated that liberalization had a delayed effect on GDP growth rate in the long term. Similarly, Kemal et. al. (2002) conducted research on the macroeconomic determinants of growth in Pakistan by examining variables such as physical capital investment, population growth, government consumption, inflation, and trade liberalization which were expected to have a significant influence on the growth rate. The OLS technique was used for estimation during the time period 1959-60 to 2000-01.

The empirical findings indicated that the influence of openness on economic growth is insignificant. This is mainly due to inconsistent and unavailable data on various crucial variables, as well

as the presence of political, institutional, and infrastructure challenges encountered by Pakistan. Both studies mentioned earlier share a common viewpoint that trade liberalization impacts distinct aspects of economic development in diverse ways, attributed to varying government policies and institutional factors.

The impact of trade liberalization can vary depending on the specifications of models and estimation techniques. Other studies also support this conclusion. For instance, Irwin et al. (2002) discovered that countries with more open economies tend to have higher per capita income when examining the relationship between trade liberalization and income growth in countries engaged in bilateral trade over different time periods using the instrumental variable (IV) technique of estimation. Mohsin et al. (2001) aimed to explain how openness affects poverty levels in Pakistan from 1963-64 to 1993-94. Their study demonstrated that poverty decreased with trade liberalization in Pakistan by utilizing the head count index method to measure poverty and representing openness as the sum of imports and exports as a percentage of GDP. Similarly, Yang and Huang (1997) argued that reducing economy-wide tariffs leads to a more equitable distribution of income in China, as evidenced by their use of a Computable General Equilibrium (CGE) model.

In a study conducted by Waczairg (2001), empirical evidence was gathered to examine the relationship between trade liberalization and economic growth in Pakistan. The investigation focused on six different channels of growth and their impact on trade liberalization. This study analyzed data from 57 countries over a period of 1970-1989 and used the simultaneous equations technique to estimate the parameters through three stage least squares.

The study revealed that trade openness has a positive effect on

growth through five factors: black market premium, manufactured exports, investment rate, foreign direct investment, and macro policy quality. However, it has a negative and insignificant impact on growth through government size (measured by government consumption). Investment seems to be the most significant way in which trade liberalization affects growth. Most of the studies reviewed so far have analyzed the impact on various development indicators separately.

The main focus on development often only focuses on economic growth, disregarding other factors. While there is a positive link between trade liberalization and economic growth, it alone is not sufficient to promote development. To fully comprehend the overall impact of trade liberalization on economic development, one must take into account various factors. This research investigates significant aspects of development in Pakistan from 1960-2003, such as per capita GDP, income inequality (measured by the Gini coefficient), poverty levels, and employment.

This study presents new findings on the economic consequences of trade liberalization in Pakistan. It utilizes a simultaneous equations model to examine the impacts of different factors. The study is organized into five parts. Part two investigates the trade policies implemented in Pakistan that are associated with liberalization. Part three outlines the model specification and estimation procedure. Part four discusses the data and how various variables were created. Finally, part five elucidates the empirical results.

The text examines the beginnings of trade liberalization in Pakistan, particularly focusing on its early economic years. At that time, Pakistan had a limited industrial foundation and was primarily reliant on agriculture. Additionally, there were challenges with infrastructure and political instability. The primary objective during this period was to bolster the industrial

sector by establishing a strong base. Several factors including black market premium, manufactured exports, investment rate, foreign direct investment, macro policy quality, and government size were considered. The study concludes by highlighting specific policy implications.

Pakistan implemented a restricted trade system and protected its domestic industries by imposing high tariff and non-tariff barriers. In the 1960s, efforts were made to promote industrial growth, resulting in significant expansion of large-scale manufacturing sectors within the country. Although the protected trade system was beneficial during this period, further actions were taken to enhance industrial exports. These actions comprised maintaining an artificially high exchange rate, offering export incentives, granting preferential credit access to export-oriented industries, and automatically renewing import licenses.

Industrial production and exports saw substantial growth in the 1960s but slowed down in the next decade due to nationalization of industries. However, the government introduced three trade liberalization measures during this period to boost exports. These measures included a 57% devaluation of the Pakistani Rupee in 1972, elimination of the export bonus scheme, and termination of restrictive licensing.

Pakistan implemented a new trade policy in 1987, leading to significant changes in its trade policies. These changes resulted in export growth, particularly in the manufacturing sector. One notable change was the reduction of tariff slabs from 17 to 10 and the replacement of commodity-based sales taxes with a uniform tax. The government aimed to involve the private sector more actively in the economy, enhance competitiveness and efficiency in the domestic industrial sector, and promote exports. To achieve these goals, fiscal incentives such as tax holidays, tariff reductions, and profit-enhancing opportunities were provided to exporters. For example,

maximum tariffs decreased from 225 percent in 1986-87 to 70 percent in 1994-95, and custom duty slabs reduced from 13 to 5. Additionally, Pakistan maintained a flexible exchange rate system throughout this period.

Between 2000 and 2003, various business policies were implemented, such as liberalization, deregulation, and cost reduction. These policies emphasized the importance of maintaining a stable macroeconomic framework in terms of inflation, interest rate, and exchange rate. Additionally, there was a greater focus on promoting previously overlooked service exports, which has now become an integral part of the country's trade policy. The government has set targets for this year's exports and imports at US $12.1 billion and 12.8 billion respectively, aiming to reduce the trade deficit to less than US$1.0 billion (GOP, 2004).

The impact of trade liberalization on Pakistan's economic development will be assessed based on its effects on per capita gross domestic product (GDP), poverty levels, income inequality, and employment opportunities.

These indicators of development are derived from Dudley Seers's definition of development in 1972. The idea is that these indicators not only impact each other, but are also influenced by each other. For instance, the employment level and per capita GDP are mutually reliant. Additionally, per capita GDP and the Gini coefficient are linked according to Kuznet's hypothesis. From an econometric standpoint, this interdependence among the endogenous variables poses a challenge of simultaneity.

The chosen variables necessitate the formulation and estimation of the model in a way that yields valid results. A simultaneous equations model has been specified and estimated using the 2SLS regression technique. The equations are as follows:

LPt = ? 0 + ? 1LGt+ ? 2 LPGDPt + ? 3LEMPt+

? 4LTLt + ? t

LGt = ? 0 + ? 1LPGDPt + ? 2LCPIt + ? 3LTLt + ? t

LPGDPt = ? 0 + ? 1LEMPt + ? 2LHKt + ? 3LINVt + ? 4LTLt + ? 5 TG + ? t

LEMPt = ? 0 + ? 1LPGDPt + ? 2LWt + ? 3LINVt + ? 4 TG + ? 5LTLt + ? t (1) (2) (3) (4)

The text explains the variables used in the context. The variable P represents poverty, G represents household Gini coefficient, PGDP represents per capita gross domestic product, EMP represents the employed labor force, inflation is measured by the CPI index, HK represents human capital, W represents real wages, INV represents the ratio of domestic investment to GDP, TG represents the type of government (1 for political government and 0 otherwise), and TL represents trade liberalization. Equation 1 illustrates how trade liberalization affects the poverty level in Pakistan. Equation 2 demonstrates the impact of trade liberalization on income distribution. The next equation determines the effect of trade liberalization on the per capita gross domestic product (PGDP).

The text below has beenand unified while maintaining the and their contents:

The model's final equation investigates the impact of trade liberalization on employment in Pakistan. It should be noted that this analysis utilizes a four-equation interconnected model. The dependent variables within these equations, which are internal variables of the model, include poverty, the Gini coefficient, per capita income, and employment level. On the other hand, the explanatory external variables consist of inflation, human capital, investment to GDP ratio, government type, real wages, as well as lagged values of PGDP and

trade liberalization index.

The text gives a summary of the variables used in the model, such as Per capita Gross Domestic Product (GDP), Poverty, Employment Level, and Gini coefficient. For Pakistan specifically, GDP represents the total value of goods and services produced in a year. Per capita GDP (PGDP) is calculated by dividing GDP by the population. Poverty is measured using the Head Count Ratio Index. Employment Level indicates the percentage of people in the workforce engaged in paid employment or self-employment.

The Gini coefficient measures income inequality based on the proportion of income received by various population segments. The variable D represents a Political Government, with a value of 1, while other situations are represented by a value of 0. Human capital is measured using primary level enrollment rates (in thousands) for the overall economy. Inflation is determined by the annual rate of price increase and is calculated using the Consumer Price Index. Real wages refer to payment made by employers to employees for their work.

The text explores the computation of real wages by dividing annual nominal wages by the corresponding real CPI. It considers both public and private investments during the study period. The text introduces two indicators to evaluate trade liberalization: the trade-GDP ratio, calculated by dividing the sum of exports and imports by GDP, and import duties as a percentage of total imports. The text also references government type, human capital, inflation, gross investment, and GDP ratio. The study investigates the correlation between trade liberalization and economic development in Pakistan.

The analysis utilizes national time series data from 1959-60 to 2002-03, with all variables measured in millions of rupees at

constant market prices using 1990-91 as the base year. Interpolated data was used for years lacking information on poverty and the Gini coefficient. Data was sourced from various outlets including the Pakistan Economic Survey, Pakistan Labor Force Survey, and the CBR Yearbook. The variables considered encompass poverty, Gini coefficient, GDP, population, Consumer Price Index, human capital, employed labor force, imports, exports, GDP deflator, wages, and import duties. The objective is to evaluate the relationship between poverty and variables like PGDP (Per Capita Gross Domestic Product), EMP (Employment), and trade liberalization.

The repercussions of an oversupply of goods and services are expected to include a decrease in prices, resulting in an enhanced standard of living. Income distribution, which gauges income inequality, can be affected by factors like PGDP (per capita gross domestic product), inflation, and trade liberalization. The Kuznets hypothesis proposes that PGDP can either raise or lower the Gini coefficient value, indicating a U-shaped relationship between them. Furthermore, it is anticipated that significant inflation will have a positive correlation with the Gini coefficient.

Predicting the impact of trade liberalization on income distribution in Pakistan is difficult. This policy change could either worsen or improve income distribution. The dependent variable, per capita GDP, is a measure of a country's economic development. A high and increasing per capita GDP usually indicates economic progress. Trade liberalization, employment (EMP), and human capital are expected to positively affect per capita GDP. Including investment in the model is justified as it can enhance per capita GDP through the multiplier effect.

The model incorporates a dummy variable to depict the government type in different time periods and its influence

on economic development. The variable aims to capture the impact of political and institutional factors on development. A democratic government is expected to have a positive effect, while a military regime is expected to have a negative effect. Furthermore, it is anticipated that PGDP will positively impact labor force employment. The type of government also significantly affects employment outcomes.

Free trade is anticipated to have a favorable influence on employment by granting accessibility to low-cost raw materials and capital machinery, thereby promoting development opportunities within a nation. To handle the issue of model over identification, this study employs the two-stage least square (2SLS) method for estimation. The 2SLS approach entails substituting the endogenous explanatory variable with a linear combination of predetermined variables in the model and employing them as substitutes for explanatory variables.

The 2SLS method is similar to the instrumental variable method of estimation, as it uses a linear combination of predetermined variables as instruments or proxies for endogenous variables. This technique involves two stages. In the first stage, structural equations are computed by regressing endogenous variables on all predetermined variables, removing interdependence among variables. Structural equations express endogenous variables solely in terms of predetermined variables and stochastic disturbances.

The OLS technique is applied to the reduced form equation to obtain the structural or reduced form coefficients. These coefficients are then used in the primary equations. The second stage of estimation involves estimating these equations again using the OLS technique to obtain unbiased and consistent coefficients. The regression analysis is performed using two models, one using an openness index and the other using the share of import duties in total imports as a

measure of trade liberalization. However, only the results for the former measure are quoted as they are more precise.

The estimated model's results are available in Table 1, which presents various variables expressed in logarithms. The openness index, representing trade liberalization, is determined by the sum of export and import as a percentage of GDP. While additional information on import duties as a percentage of total imports can be found in the appendix, the focus of the discussion is on openness as a measure of trade liberalization.

Table 1 showcases estimates for different equations in the model alongside their corresponding t-values and levels of significance. The first column lists variable names, while columns two to five provide estimates for equations with dependent variables such as poverty (in logarithm form), income inequality, GDP per capita, and employment.

Most results demonstrate compatibility and satisfaction regarding coefficient signs and sizes. Additionally, these equations have relatively high adjusted R2 values: 0.88 , 0.61 , 0.6 , and 0.98 respectively.

To address detected autocorrelation through the Durbin Watson test, an auto regressive scheme two (AR (2)) was utilized.

Assessing the impact of trade liberalization on various development indicators is crucial for academic and practical policy purposes; however, according to the findings presented in Table-1, trade liberalization has not effectively reduced poverty in the country.This indicates that despite efforts to promote trade liberalization, poverty has increased.

The impact of PGDP on poverty levels has been substantial. Poverty rates have decreased by 1.7% for every 1% increase in PGDP, highlighting a strong correlation between poverty and PGDP. Mohsin et al.'s (2001) previous research also found similar results regarding the reduction of poverty with an increase in

PGDP. Employment, considered a key factor in poverty reduction, has shown a significant negative effect at the 1-percent level of significance.

The country's development and poverty reduction heavily rely on employment. A small increase of one percent in job opportunities has led to a significant 4 percent decline in poverty rates. Despite trade liberalization, poverty levels have not decreased possibly due to insufficient institutions, political instability, and economic fluctuations. It is worth noting that the main objective of implementing trade liberalization is not to eliminate poverty.

The distribution of income, as the second development indicator, is influenced by trade liberalization. It has a statistically significant positive impact on income inequality, causing it to increase by 0.08%. These results align with expectations and are considered satisfactory. Liberalization leads to a decrease in the proportion of labor in production and an increase in capital. As a result, returns change and income becomes more concentrated among capital owners. The PGDP also reflects this trend.

The study utilized AR (2) instead of AR (1) to tackle auto-correlation. The results reveal that trade liberalization and economic development in Pakistan have resulted in a noteworthy decrease in income inequality. More precisely, a 1 percent rise in PGDP corresponds to a 0.8 percent drop in income inequality. However, unlike PGDP which has reduced it, inflation has adversely affected income distribution by increasing inequality throughout the study period in Pakistan.

The research confirms that inflation's impact on income distribution aligns with Fischer's findings (1993). Moreover, trade liberalization has a significant effect on PGDP. Surprisingly, contrary to expectations, an increase in liberalization has caused a decrease in PGDP. This unexpected

outcome may be attributed to certain policies adopted for investment and import substitution, which have impeded economic growth and resulted in a lower level of PGDP despite the presence of trade liberalization.

Another potential explanation may be the inadequate knowledge in the subject matter.