metadata: authors: 0: author: Sinha,Rishabh
count: Bangladesh
docna: 0: docna: Long-term growth scenarios for Bangladesh
docty: Policy Research Working Paper
subtopic: Economic Theory & Research,Labor & Employment Law,Industrial Economics,Labor Markets,Food Security,Economic Growth
teratopic: Public Sector Development,Macroeconomics and Economic Growth,Industry
abstracts: cdata!: Bangladesh has achieved robust economic
            growth over the past 10 years, with real GDP growing by more
            than 6 percent on average each year. This paper investigates
            whether the country will be able to maintain such high
            levels of growth going forward. A simple growth model
            calibrated to the Bangladesh economy is used to analyze
            various growth scenarios. The main finding of the paper is
            that it is crucial for the country to focus on reforms to
            raise total factor productivity (TFP) growth, to sustain the
            high real GDP growth seen in the recent past. The country
            will fail to achieve high growth in absence of strong TFP
            growth despite meeting the levels of investment as outlined
            in the Seventh Five Year Plan. The model is also used to
            gain insights on government debt sustainability given
            different growth scenarios. The analysis highlights the
            significance of meeting revenue targets in maintaining
            sustainability, considering the planned expansion in expenditures.
geo_reg_key: 517191,517198,517212
repnme: repnme: Long-term growth scenarios for Bangladesh
display_title: Long-term growth scenarios for Bangladesh
listing_relative_url: /research/2017/01/27123019/long-term-growth-scenarios-bangladesh
topicv3: Agriculture and Food Security m1326205 435,Economic Growth m1326241 471,Labor Force Participation m1504050 2746,Working Age Population m1504053 2749,Labor Productivity m1504060 2756
publishtoextweb_dt: 2017-01-30T00:00:00Z
historic_topic: Public Sector Development,Macroeconomics and Economic Growth,Industry
no_of_pages: 40
author_keys: 0: author_key: 1411342
model_extractions: WPS7952 Policy Research Working Paper 7952 Long-Term Growth Scenarios for Bangladesh _Rishabh Sinha_ Development Research Group Macroeconomics and Growth Team January 2017
Policy Research Working Paper 7952

# **Abstract**

Bangladesh has achieved robust economic growth over the past 10 years, with real GDP growing by more than 6 percent on average each year. This paper investigates whether the country will be able to maintain such high levels of growth going forward. A simple growth model calibrated to the Bangladesh economy is used to analyze various growth scenarios. The main finding of the paper is that it is crucial for the country to focus on reforms to raise total factor productivity (TFP) growth, to sustain the high real GDP growth seen in the recent past. The country will fail to achieve high growth in absence of strong TFP growth despite meeting the levels of investment as outlined in the Seventh Five Year Plan. The model is also used to gain insights on government debt sustainability given different growth scenarios. The analysis highlights the significance of meeting revenue targets in maintaining sustainability, considering the planned expansion in expenditures.

This paper is a product of the Macroeconomics and Growth Team, Development Research Group. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The author may be contacted at rishabhsinha@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
# **Long‐Term Growth Scenarios for Bangladesh**

Rishabh Sinha<sup>1</sup> JEL Classification: O40, O53, J24 Keywords: Long‐term Growth, Bangladesh, TFP Growth, Labor Productivity

> 1 I am grateful to Afroza Alam, Hans Beck, Simon Davies, Ralph Van Doorn, Zahid Hussain, Sheikh Tanjeb Islam, Frederico Sander, Muhammad Waheed and workshop participants from the Ministry of Finance, Bangladesh and the Bangladesh Bank for many useful insights and suggestions. The World Bank’s Long‐Term Growth Model (LTGM) has been used extensively for the quantitative analysis presented in the paper. The LTGM was developed by Steven Pennings and Leonardo Garrido, based on Hevia and Loayza (2012), and with input and support from Vinaya Swaroop, Jorge Guzman, and Diego Barrot. Please contact the author or Steven Pennings (spennings@worldbank.org or LTGM@worldbank.org) for further information about the LTGM.
# **1. Introduction**

Bangladesh has seen robust economic growth during the last decade, with real GDP growing by more than 6 percent on average every year during 2006 – 2015. Additionally, the economy has seen a long‐term acceleration in growth since the late 1970s when the real GDP was growing by just over 4 percent annually. The acceleration in real GDP growth has also translated to an acceleration in real GDP per capita growth as the gap between real GDP growth and population has been widening over time.<sup>2</sup> Beginning from $352 in 1980, real GDP per capita (measured in 2010 US dollars) crossed $700 in 2008 and is on mark to cross $1,000 next year. The sustained economic growth during the last few decades has helped the country graduate from a low‐income country to a lower‐middle‐income country as classified by the World Bank (World Bank, 2015).

<!-- Start of picture text --> 8<br>6<br>4<br>2<br>0<br>‐2<br>‐4<br>‐6<br>GDP GDP per Capita<br>Source: World Development Indicators<br>Average Annual Growth Rate (%)<br>1961 ‐ 1965 1966 ‐ 1970 1971 ‐ 1975 1976 ‐ 1980 1981 ‐ 1985 1986 ‐ 1990 1991 ‐ 1995 1996 ‐ 2000 2001 ‐ 2005 2006 ‐ 2010 2011 ‐ 2015<br><!-- End of picture text --> To better understand the sustained growth achieved by the country, it is useful to explore how some of the key growth drivers have evolved during this period. Capital accumulation has been a key driver of economic growth for many countries and Bangladesh is no exception to this phenomenon. Bangladesh has realized continued rise in the investment share of GDP during the last 35 years. The investment share of GDP has almost doubled from 14.4 percent of GDP in 1980 to 28.9 percent of GDP in 2015. Most of this increase has been driven by gains in private investment. With respect to its Asian neighbors, the country currently has a higher investment rate compared to Pakistan and Nepal but lags behind China and India.

The country has witnessed many changes in the labor market that have been important for growth. The demographic transition has led to a decline in the dependency ratio with the share of working age population rising continuously over time. Starting from 52 percent of the

> 2 Real GDP per capita saw negative growth during 1960 – 1980, but has been rising ever since.

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total population in 1980, the working age population share grew by more than 13 percentage points in the last 35 years. The growth received further tailwind from increasing participation rates. The aggregate participation rate rose from approximately 45 percent in the mid‐1970s to over 60 percent in the 2010s, largely due to a massive jump in the female labor force participation rate, which grew from a low base of 12 percent in 1989 to 30 percent in 2013. What has been most encouraging is that not only the quantity but also the quality of labor resources has been rising over time. The Penn World Table (PWT) human capital index for <!-- Start of picture text --> 35 Population ages 15 ‐ 64 (% of Total Population)<br>70<br>30<br>Total<br>25 65<br>Private<br>20<br>60<br>15<br>10<br>55<br>5<br>0 50<br>Source: World Development Indicators Source: World Development Indicators<br>Investment Share of GDP (%)<br>1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 2015 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014<br><!-- End of picture text --> Bangladesh has grown by more than 1.5 percent per year on average during 1990 – 2010.

Apart from growth in underlying factors of production – capital and labor – economic growth can also be derived from advances in technology or through an efficient use of existing resources. The growth in the productivity of resources, or Total Factor Productivity (TFP), has been an important driver of growth for many countries.<sup>3</sup> The TFP growth rate for Bangladesh during 2001 – 2011 has just been above zero implying that the strong growth seen during the period was not aided by either technology adoption or through efficiency in resource allocation. On the other hand, India and China, which also realized healthy economic growth during the same period, were aided significantly by productivity with TFP growing by 1.3 percent and 2.9 percent on average each year respectively. However, the uptick in TFP growth since later 2000s is encouraging and continued reforms can help the country to move into an era of sustained positive TFP growth.

The important question going into the future is whether the country can continue on its path of accelerating growth or not. The goal is to identify areas that need reform and quantify the relative merit of alternative growth strategies. Such an analysis will help isolate factors that are most likely to be the key drivers of growth. In this paper, I use the World Bank’s Long‐Term Growth Model (LTGM) to answer these questions. The LTGM (Pennings 2016) is a simple

> 3 The estimated TFP growth series is usually volatile and is also sensitive to the method of estimation. TFP is estimated as a residual after accounting for all factors of production, and the estimates across studies are bound to differ if they employ a different production function or measure factors of production differently. For example, estimates of TFP will be different for a study that accounts for human capital based on schooling compared to a study that does not account for human capital gains that stem from schooling.

3
growth model, developed in spirit of Solow (1956) – Swan (1956) growth models, and uses investment, savings and productivity as building blocks and ties these variables to economic growth. The model also includes labor market forces that are important in driving growth together with an external sector through which additional investment can be sourced. An important finding from the growth equation obtained after solving the model shows that investment becomes less effective in generating growth with an increase in the capital‐to‐ output ratio. This implies that the same level of investment share of output will generate lower growth if capital in the economy is growing faster than output. Hence, an investment‐led growth strategy in absence of reforms that focus on growth of productivity, human capital and participation will eventually run out of steam.

The model is calibrated for Bangladesh by matching some of the standard moments in growth literature. An appealing feature of the model is that it is fairly parsimonious with regards to the parameters. Nonetheless, robustness checks are performed around the parameter values used in the benchmark exercises. The calibrated model is then used to perform several quantitative exercises that feature different scenarios on how the drivers of growth evolve over time.

The main finding of the analysis is that for Bangladesh to sustain a high real GDP growth rate, it is essential that the country focus on reforms that drive TFP growth. An investment‐led strategy that boosts investment share to 35 percent by 2020 coupled with improvements in efficiency of public capital will deliver GDP growth of 5 percent for the next decade. However, maintaining such level of investment will deliver lower than 5 percent GDP growth beyond 2025 in absence of TFP growth as high capital‐to‐output ratio will make investment less‐and‐less productive in generating growth. Alternatively, a sustained high GDP growth path in absence of TFP growth will require massive investments that exceed the levels targeted by the government. More alarmingly, the required investments will soon reach levels that are unrealistic to attain.

Finally, the model can also be used to infer what the implied growth paths spell for the sustainability of government debt position. The country has a low government debt to GDP ratio which stood at 34 percent at the end of 2015. The analysis finds that the government debt situation is sensitive to government operations and that meeting tax revenue targets is essential to keep the government debt to GDP ratio in check. The government debt sustainability will face additional risk if the government overshoots its expenditure without making much progress on the revenue front.

# **2. A Simple Growth Model**

In order to quantitatively analyze the growth prospects of Bangladesh, I use a version of the World Bank’s LTGM which is an extension of the Solow (1956) – Swan (1956) growth 4
t Ky

> ¥,t **=** A,K; (yt) B hy . At

B

|

It Kty1 = 6 Mt Le = Pert Pt We Nt yet = P,0,A_k,1-B,Bt
Ye Ye ky t ttl <u>yee</u> (ep <u>w A kear\F</u> (hear \? t tt+1 1+ Tyt+1 = (1 + Ipt+i1)(1 + Jut+i)(1 + Datei) + utr) (A + Gnesi) x t ttl Ix,t+1 ~~— })|—]}~~ = A -46 ~~)(—~~ ] ~~+— (==) (=)~~ <u>Lt</u> ( ~~(7)~~ <u>Ly LtI,</u> ky (1 ~~<u>(a</u>~~ + Terri )(1 + Iwe+i)(1 + Ipt+i1)(1 + Jut+1) =(1-6)+ ~~<u>RA</u> (¥)~~ Jk,t+1 ~~Tt~~ <u>(o-o</u> ~~<u>nlf</u>~~ (1 ~~<u>¥p</u>~~ + Ixt+1) 7 <u>(4+9n,t+1)(14+9p,t41)(14+90,t+1)</u>

Test = Jat+it B(Gp,t+1 + Jo,t+1 Int+1) +(1-f) ~~<u>EsTt</u>~~ Yt — 6 — anon
The above equation offers many insights regarding the drivers of growth. First, the TFP growth �� has the largest direct effect on growth where a 1 percentage point increase in TFP leads to a 1 percentage point increase in growth rate of output per capita. Second, the production function parameter � plays an important role in determining the relative importance of capital and labor growth in driving aggregate growth. The larger the labor share of income, the more responsive is the output growth to increases in participation rate, working age population to population ratio and human capital per worker. Conversely, the larger the labor share of income, lower the effect of capital accumulation in generating growth. Finally, it is important to note that keeping all else constant, the same level of investment share of output can lead to different output growth rates depending on the level of the capital‐to‐ � output ratio of the economy. Investment becomes less effective as the capital‐to‐output ~~�~~ � ~~�~~ ratio rises in the economy. This implies that the same level of investment share of output will generate lower growth if capital in the economy grows faster than the output. Hence, an investment led growth strategy in absence of reforms that focus on growth of productivity, human capital and participation will eventually run out of steam.

In the next section, I begin with the quantitative analysis and examine various growth scenarios for the country. The first step of the analysis requires the calibration of the model to the Bangladesh economy. Following calibration of the model, the long‐term growth scenarios for the country are considered by asking two related questions. First, how much growth can be achieved under various reasonable paths of growth drivers and second, what time paths of growth drivers, in particular investment, is essential to realize a given growth path.

# **3. Quantitative Analysis**

Each period of the model corresponds to a year which implies that all growth rates are annual in nature. A desirable feature of the model is that it is parsimonious with regards to parameters. There are only three parameters that need calibration – labor share of income � , �� depreciation rate � and initial capital‐to‐output ratio ~~.~~ ��

- **Labor share of income:** ���. ��. The Penn World Tables 8.1 does not contain the labor share data for the case of Bangladesh. An alternative source that provides guidance for this parameter is the Global Trade Analysis Project (GTAP). The GTAP database contains information that can be used to calculate the aggregate labor share.<sup>5</sup>

<!-- Start of picture text --> 0.60<br>0.50<br>0.40<br>0.30<br>5 See Hertel, Tsigas and Narayanan (2002) on details regarding the calculation of labor shares in the GTAP 0.20<br>database.<br>0.10<br>7<br>0.00<br>Bangladesh LMI ‐ Mean LMI ‐ Median<br>Labor Share of Income<br><!-- End of picture text -->

**Source: PWT 8.1, GTAP**
The most recent year for which data is available is 2011, which is used to arrive at the labor share of 0.51 for Bangladesh. The figure below compares the labor share of income of Bangladesh to the mean/median labor shares of lower‐middle income countries obtained from PWT 8.1 for the year 2011. The labor share of the country lies close to the mean/median of the lower‐middle income countries though somewhat lower. In the robustness exercises, I show how alternative values of � affect the results of the analysis.

- **Depreciation Rate:** ���. ��� **.** The annual depreciation rate of capital stock is sourced from the PWT 8.1. The PWT 8.1 classifies capital stock into six different categories with each category having a different rate of depreciation. A somewhat lower depreciation rate for Bangladesh is rooted in the fact that the country has larger share of capital stock in assets that depreciate slowly relative to assets that have a much higher rate of depreciation such as computers, software etc. The aggregate depreciation rate for the country is likely to inch upward as the capital mix shifts towards assets that have a higher depreciation rate. The robustness exercises discuss the sensitivity of the findings to the choice of higher depreciation rates.

- ��

- **Initial capital‐to‐output ratio:** ��. ��. The initial capital‐to‐output ratio is calculated ��

- using the capital stock and GDP data from the PWT 8.1. The most recent year for which data is available from the PWT 8.1 is 2011 which is used to calculate the specified value of capital‐to‐output ratio. The figure below compares the capital‐to‐output ratio of the country with some of its neighbors. The capital‐to‐output ratio of the country is lower compared to China driven by the fact that China has made massive investments in capital stock over the last few decades. Though still in range with other neighbors except Nepal, the capital‐to‐output ratio is somewhat higher for Bangladesh. As seen in

<!-- Start of picture text --> 4.0<br>3.5<br>3.0<br>2.5<br>2.0<br>1.5<br>1.0<br>0.5<br>0.0<br>Bangladesh China India Nepal Pakistan Sri Lanka<br>Capital‐to‐Output Ratio<br><!-- End of picture text -->

**Source: PWT 8.1**

equation (8), a higher value of the capital‐to‐output ratio puts downward pressure on the growth impact from increasing investment.

8
# **3.1 Growth Consistent with Reasonable Time Paths of Growth Drivers**

Having calibrated the model, I now move to analyze the long‐term growth scenarios for the country. The first approach consists of choosing reasonable paths of drivers of growth and uses the model to solve for the resulting growth paths. Specifically, I assume the following time paths:

- **Growth rate of human capital per worker:** �� ��. �% **.** The historical trend in human capital index from the PWT 8.1 provides guidance regarding the reasonable path of human capital per worker going forward. The PWT 8.1 reports the index based on the Barro‐Lee method that takes into account both the years of schooling as well as returns on education. The PWT 8.1 data is available for the period 1990 – 2010. After reaching a peak during the second half of 1990s, the growth of human capital index has been on a downward trend. The average growth rate stood just below 1.4 percent during the period 2006 – 2010. It seems likely that the growth rate of human capital will continue its gradual decline with contribution from gains in primary education diminishing as it reaches absolute levels. As such, the human capital per worker growth rate is assumed to be 1.3 percent per annum going into the future.

<!-- Start of picture text --> 2.0<br>1.5<br>1.0<br>0.5<br>0.0<br>1991 ‐ 1995 1996 ‐ 2000 2001 ‐ 2005 2006 ‐ 2010<br>Source: PWT 8.1<br>Growth Rate of HC Index (%)<br><!-- End of picture text -->

- **Growth rate of TFP:** �� ��%. A TFP index for the country is calculated using the data and methodology listed in PWT 8.1 and using the labor share of 0.51 obtained from the GTAP database. The growth rate of TFP is generally volatile and it is also true for the case of Bangladesh as seen in the figure below. The TFP was on an upward trend from the 1980s till it suddenly dropped in 2001. After remaining in the negative territory for another two years, the TFP growth started trending upwards again. The average growth rate of TFP during 1991 – 2011 has barely managed to remain in the positive

9
territory. Given the volatile nature of TFP growth and the average recorded for the 1991 – 2011 period, it is assumed that the country will not experience any meaningful TFP growth in the long‐term.

<!-- Start of picture text --> 3<br>2<br>1<br>0<br>‐1<br>‐2<br>‐3<br>‐4 1991 ‐ 2011 Average<br>‐5<br>1980 1985 1990 1995 2000 2005 2010<br>Source: PWT 8.1, GTAP<br>Growth Rate of TFP (%)<br><!-- End of picture text -->

- **Growth rate of population:** ��. The population projections have been sourced from the World Bank’s Human Development Network estimates. According to the Human Development Network, the annual population growth rate for the country will decline from present 1.2 percent to 1.0 percent by 2021 and 0.7 percent by 2030.

<!-- Start of picture text -->
1.4 Working Age Pop to Pop 70<br>1.2<br>69<br>1.0<br>68<br>0.8<br>Population 67<br>0.6<br>66<br>0.4<br>65<br>0.2<br>0.0 64<br>Source: World Bank Human Development Network<br>Growth Rate of Population (%) Working Age Pop to Population (%)<br>2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030<br><!-- End of picture text -->

- **Growth rate of working age population to population ratio:** �� **.** In addition to the population forecasts, the Human Development Network also provides projections for the working age population of men and women separately. The projections indicate that the aggregate working age population to population ratio in Bangladesh will continue to rise and reach almost 70 percent by the year 2030, a gain of 4 percentage points from the current levels.

10
There are two more time paths that are needed to run the growth simulations – investment share of GDP �� and participation rate ���� . Both these drivers of growth are ~~�~~ �� ~~�~~ expected to play a big role going forward and have been identified as such by the policy makers. For this reason, I consider different scenarios for their time paths that help in identifying their relative importance.

- ��

- **Investment share of GDP: .** Bangladesh has realized continued increase in the ��� ~~�~~

- investment share of GDP during the last 35 years. The investment share of GDP has almost doubled from 1980 to 2015 with most of the increases coming from private investment. Needless to say, capital accumulation has been an important driver of growth in the country. This point is illustrated in the graph below which shows the average GDP per capita growth rate during 2011 – 2015 against the average investment share during the same period for more than 200 countries for which data is available from the World Development Indicators database.<sup>6</sup> The relationship between the two variables is positive and highly significant. However, a more important

<!-- Start of picture text --> Correlation = 0.37***<br>CHN<br>BGD LKA IND<br>NPL<br>PAK<br>0 20 40 60<br>Average Investment Share of GDP, 2011 - 2015 (%)<br>Source: World Development Indicators (***Significant at 1%)<br>10<br>5<br>0<br>-5<br>Average GDP per Capita Growth., 2011 - 2015 (%)<br>-10<br><!-- End of picture text --> question is whether capital accumulation can deliver a sustainable high level of growth going into the future.

Average investment as a share of GDP for the country during 2011 – 2015 was upwards of 28 percent and the country delivered higher growth than what is expected at that level of investment. The country has a higher investment rate compared to

> 6 Note that for some countries data for 2015 are not available, in which case the average reflects the average during 2011 – 2014.

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Pakistan and Nepal but lags behind China and India. This suggests that the country has some room to expand its investment share of GDP. However, as can be seen from the graph below, the deficit in investment share with respect to India is not due to low public investment in Bangladesh. Average public investment as a share of GDP during 2011 – 2014 outpaced that of India by more than 2.5 percentage points. The targets from the 7<sup>th</sup> Five Year Plan are used to chart a reasonable path of investment. Specifically, I assume that the aggregate investment share of GDP increases from the present levels to 34.4 percent of GDP by year 2020 and remains at that level beyond 2020. This is based on the plan targets on public investment which rises from 6.5 <!-- Start of picture text --> 50<br>40<br>30<br>20<br>10<br>0<br>Bangladesh China* India** Nepal** Pakistan Sri Lanka<br>Aggregate Private Public<br>Source: World Development Indicators<br>*Aggregate average of 2011 ‐ 2014, **All measures average of 2011 ‐ 2014<br>Investment Share of GDP (%)<br><!-- End of picture text --> percent of GDP in 2016 to 7.8 percent of GDP by year 2020. This implies that private investment as a share of GDP expands by approximately 3 percentage points to reach 26.6 percent by 2020. I assume that both public and private investment continue to remain at the same level beyond 2020.

With regards to investment, there is a concern that public investment is not as efficient as private investment. This means that a percentage point expansion in public investment will deliver lower growth compared to a percentage point expansion in private investment. On the other hand, it is possible to generate additional growth by increasing the efficiency of public investment. To capture the differences in efficiency across public and private investment, it is assumed that a unit of public investment ��� equals only a fraction �∈�0,1� of private investment ��� which is perfectly efficient. The total effective investment �� is given by �� ����� ���� (9) There are many studies that have studied the efficiency of public sector (for example Afonso, Ludger Schuknecht and Tanzi (2005, 2010) etc.). The quantitative findings from these studies can be used to discipline the parameter governing the efficiency of public investment � . Afonso, Ludger Schuknecht and Tanzi (2010) report that for the sample countries, the same level of public sector output can be produced 12
using 41 percent less resources on average. This implies a capital efficiency of 59 percent. The efficiency of public investment for Bangladesh is assumed to be a bit lower than the mean efficiency at 55 percent, owing to the fact that the developing countries in the sample have lower efficiency rates.

- **Participation rate:** �� **.** The aggregate participation rate is the weighted average of the male and the female participation rates. The male labor force participation rate in the country has remained near 80 percent for many decades and is similar to what is observed in many countries worldwide. On the other hand, the female labor force participation stands at 34 percent and has considerable room for improvement. The country has achieved around 10 percentage points increase female labor force participation during the last decade and provides basis for further expansion going forward. However, I analyze the prospective expansion in female labor force participation separately in order to isolate its impact on growth.

I construct the following four scenarios in order to quantify the growth impact of improvements in investment and female labor force participation. Note that all other variables like growth rate of human capital per worker, growth rate of TFP etc. are unchanged across scenarios and follow the time path as previously defined.

- **Baseline Scenario:** Public and private investment share of GDP rises according to 7<sup>th</sup> Five Year Plan targets till 2020 and remains at 2020 level going forward. The efficiency of public investment remains at 0.55 throughout and there is no change in the female labor force participation rate.

- **Efficiency Scenario:** Public and private investment follow the same path as in Baseline Scenario and the efficiency of public investment grows linearly from 0.55 in 2015 to 1.00 in 2020. There is no change in the female labor force participation rate.

- **Participation Scenario:** Public and private investment follow the same path as in Baseline Scenario and the female labor force participation rate grows linearly from 34 percent in 2015 to 45 percent in 2020. There is no change in the efficiency of public investment.

- **Efficiency + Participation Scenario:** Public and private investment follow the same path as in Baseline Scenario and the efficiency of public investment grows linearly from 0.55 in 2015 to 1.00 in 2020. The female labor force participation rate also grows linearly from 34 percent in 2015 to 45 percent in 2020.

The simulation results corresponding to the four scenarios are shown in the figures below. Apart from demographic changes, the only drivers of growth operating in the Baseline Scenario are capital accumulation and growth of human capital per worker. The GDP growth rate increases marginally till 2021, driven by expanding the investment share of GDP. The GDP growth rate remains below the 5 percent mark for the entire period till 2021. The growth rate starts declining past 2021 and falls below 4 percent in 2028. In addition to the forces driving growth in the Baseline Scenario, the linear rise to efficiency of public investment provides 13
further push to economic growth. Similar to the Baseline Scenario, the growth rate increases till 2021 and is slightly higher than the Baseline Scenario. The GDP growth rate peaks in 2021 <!-- Start of picture text --> 10 Real GDP Growth (%) 10 Real GDP Growth (%)<br>Baseline Scenario Efficiency Scenario<br>9 9<br>8 Plan Target 8 Plan Target<br>7 7<br>6 6<br>5 5<br>4 4<br>3 3<br>2 2<br>10 Real GDP Growth (%) 10 Real GDP Growth (%)<br>Participation Scenario Efficiency + Participation Scenario<br>9 9<br>8 Plan Target 8 Plan Target<br>7 7<br>6 6<br>5 5<br>4 4<br>3 3<br>2 2<br>2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030<br>2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030<br><!-- End of picture text --> under both scenarios in which the growth under the Efficiency Scenario outperforms the growth under Baseline Scenario by more than half a percentage points. Even though public investment is a small share of the aggregate investment, an increase in its efficiency has non‐ trivial impact on economic growth.

The efficiency of public investment is unchanged under the Participation Scenario. Instead, the aggregate participation rate rises driven by improvements in female labor force participation. The growth rate under Participation Scenario rises somewhat till 2020 and its behavior is very similar to the growth under the Baseline Scenario. However, the linear increase in the female labor force participation rate means that growth is higher compared to the Baseline Scenario. The 11 percentage point increase in female labor force participation spread across 5 years on average adds more than 1 percentage point to GDP growth each year. The 14
growth rate declines by about 75 basis points in 2021 as growth in participation rate comes to an end. Like the previous scenarios, the growth rate continues to decline gradually and falls below 4 percent by 2029. The last scenario considers the joint impact of improvements in the efficiency of public capital and the female labor force participation rate. Similar to the Efficiency Scenario, the growth rate increases faster compared to Baseline and Participation. In addition, the growth rate starts at a higher level owing to the impact from the higher participation rate. The growth rate declines gradually beginning in 2022, but unlike previous scenarios, the growth rate manages to remain above the 4 percent mark by 2030.

An important point to consider here is that the growth rate under all scenarios starts declining after the first few years. Equation (8) illustrates why this happens. Keeping everything constant, an increase in the capital‐to‐output ratio will lead to lower growth. This means that if capital is growing faster than output, then the growth rate will be on a downward trajectory. The figure below plots the capital‐to‐output ratio for the different scenarios. Note that the <!-- Start of picture text --> 3.9<br>3.7<br>3.5<br>3.3<br>3.1<br>2.9<br>2.7<br>2.5<br>Baseline Efficiency Participation E + P<br>Capital to Output Ratio<br>2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030<br><!-- End of picture text --> capital‐to‐output ratio is increasing throughout for every single scenario. This rising capital‐to‐ output ratio creates drag on the growth rate. In the first few years, the negative impact of the rising capital‐to‐output ratio is offset by increases in investment share, efficiency of public capital and/or female labor force participation. However, as these sources cease to operate in the later years, the rising capital‐to‐output ratio chips away at the growth rate. In this respect, it is important to understand a secondary role of growth drivers other than investment. Not only do these drivers of growth create growth directly, they also provide downward pressure on the capital‐to‐output ratio. In this way, they indirectly insure that investment remains relatively productive in generating growth.

# **3.1.1 Introducing TFP Growth**

The important finding from the four scenarios is that the implied growth rate falls short of plan targets even under the most optimistic scenario. The average annual growth rate during 2015 – 2020 averages a little over 6 percent. It appears that achieving growth rates in excess of 15
7 percent is not possible without further contributions from other sources. An important driver of growth which is missing from the simulations is the growth in TFP. The importance of TFP growth is based on two factors discussed previously. First, as noted in equation (8) the TFP growth has the largest direct effect on growth where a 1 percentage point increase in TFP leads to a 1 percentage point increase in growth rate of output per capita and second, a growth in TFP adds to output without changing the level of capital in the economy, thereby pushing capital‐to‐output ratio down and making investment more productive. While the average annual TFP growth in the country during 2001 – 2011 has barely been upwards of zero, the upward trend during the period suggests that the country can achieve positive TFP growth rate for an extended period of time if appropriate reforms are enacted. Two additional growth scenarios are carried out to quantify the impact of TFP growth on economic growth:

- **High Growth Scenario I:** Annual growth rate of TFP = 1.0 percent

- **High Growth II Scenario :** Annual growth rate of TFP = 1.5 percent

All other variables, including efficiency of public capital and female labor force participation, are assumed to follow the time path outlined in the Efficiency + Participation Scenario.

To gauge how realistic an annual increase of 1 – 1.5 percent in TFP is, consider the finding in Bernanke and Gurnayak (2002). The authors show that only 5 percent of the countries in the world were able to achieve a TFP growth of 2 percent per year on average for during 1965 – 1995.<sup>7</sup> While the two High Growth Scenarios lie within the range of what has been achieved by other countries in the past, it is noteworthy that only a handful of countries have managed to do so. Achieving a high TFP growth for a sustained period will require a continued focus on reforms and technology advancement.

The following figure shows the result of the exercise and compares the growth scenarios in the presence of TFP growth to the Baseline and Efficiency + Participation Scenarios. With an annual TFP growth rate of 1 percent, the GDP growth rate breaches the 7 percent mark and averages around 7.15 percent during 2016 – 2020 which is just below the plan targets. The GDP growth rate declines past 2020 as female labor force participation rate stabilizes. Yet, the growth rate remains above 6.5 percent for many periods. The implied growth rate is above the plan target when TFP grows by 1.5 percent per year. The average annual growth rate under High Growth II Scenario during the plan period outpaces the average annual plan growth rate by more than 30 basis points. The growth rate remains above the 7 percent mark for many years and does not fall below 6.5 percent even after 15 years. The following table summarizes the growth outcomes under various scenarios.

> 7 The estimated average annual TFP growth for Bangladesh during the period ranged between 0.1 and 0.5 percent across the various methods considered by the authors.

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<!-- Start of picture text --> 10 Real GDP Growth (%)<br>9<br>Plan Target<br>8<br>7<br>High Growth II<br>6<br>E + P High Growth I<br>5<br>4<br>3 Baseline<br>2<br>2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030<br><!-- End of picture text -->

**Average Annual Real GDP Growth (%)**

|**Scenario**|**2016 – 2020**|**2021 – 2025**|**2026 – 2030**|
|---|---|---|---|
|Baseline|4.79|4.60|3.95|
|Efficiency|5.00|5.04|4.26|
|Participation|5.79|4.78|4.07|
|Efficiency+ Participation|6.01|5.23|4.39|
|High Growth I|7.17|6.61|5.88|
|High Growth II|7.75|7.30|6.64|
|**7**<sup>**th**</sup>**Five Year Plan Target**|**7.44**|‐|‐|

It is interesting to note that the difference in average growth rates between High Growth Scenarios I and II, and Efficiency + Participation scenario increases with time. This happens because the gap in capital‐to‐output ratios between the former and the latter increases with time as additional growth achieved via TFP increases does not add to capital accumulation.

In summary, sustaining a high growth rate requires a sustained increase in TFP growth. An investment‐led strategy coupled with improvements in efficiency of public capital will deliver growth of 5 percent for the next decade. However, maintaining an investment share of GDP beyond 2025 will deliver lower than 5 percent growth as capital‐to‐output ratios keep growing, making investment less productive.

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<!-- Start of picture text --> 3.9<br>3.7<br>3.5<br>3.3<br>3.1<br>2.9<br>2.7<br>2.5<br>Baseline E + P HG I HG II<br>Capital to Output Ratio<br>2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030<br><!-- End of picture text -->

# **3.2 Required Investment given Growth Targets**

The focus of the previous section was to obtain growth rate consistent with a set of assumptions on growth drivers. In this section, I ask what assumptions on growth drivers are required to deliver a desired time path of GDP growth. As there are multiple drivers of growth, I use the model to solve for the implied investment share of GDP assuming time paths of other drivers. The goal of the exercise is to determine whether the time path of implied investment share of GDP is feasible for the country or not.

The first step here is to choose a desired path of GDP growth and it is selected based on the 7<sup>th</sup> Five Year Plan targets. In line with the plan targets, the desired GDP growth rate increases steady from 7 percent in 2016 to reach 8 percent by 2020. The desired GDP growth path remains at 8 percent from then onward. Like in the previous exercise, four different growth scenarios are considered:

- **Baseline Scenario:** All variables, for example growth rate of human capital per worker, follow the same path as in the Baseline Scenario of the previous exercise. Note that the investment share of GDP which was an input in the previous exercise is the output of this exercise.

- **Participation Scenario:** Except female labor force participation rate, all other variables follow the same path as in Baseline Scenario. The female labor force participation rate grows linearly from 34 percent in 2015 to 45 percent in 2020.

- **High Growth Scenario I:** Except TFP growth, all other variables follow the same path as in Participation Scenario. TFP grows by 1.0 percent each year.

- **High Growth Scenario II:** Except TFP growth, all other variables follow the same path as in Participation Scenario. TFP grows by 1.5 percent each year.

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The results of the simulation are shown in the following figures. Barring demographic changes, the only driver of growth operating in the Baseline Scenario is the growth of human capital per worker. The previous exercise showed that the 7<sup>th</sup> Five Year Plan targets will fail to deliver planned GDP growth under Baseline Scenario. Not surprisingly, the figure below shows that required investment share of GDP that delivers planned growth overshoots planned investment. However, the more important finding is the stark gap in required investment and planned investment. The required investment share of GDP exceeds the planned investment share by more than 13 percentage points in 2016 and rises steadily to cross 25 percent by 2020. The required investment share rises fast over time and reaches unfeasible levels soon and reaches almost 65 percent by 2022. The gap between required investment and planned investment is somewhat lower under Participation Scenario as steady increases in female labor force participation rate share the burden of delivering high desired growth. Yet, the require investment share of GDP exceeds the planned investment share significantly and the gap between the two cross the 20 percent mark in 2020. Though lower than the required <!-- Start of picture text --> 80 Required Investment Share of GDP (%) 80 Required Investment Share of GDP (%)<br>Baseline Participation<br>70 70<br>60 60<br>50 50<br>40 40<br>Plan Target Plan Target<br>30 30<br>20 20<br>80 Required Investment Share of GDP (%) 80 Required Investment Share of GDP (%)<br>High Growth I & II<br>70 70<br>60 60<br>50 50<br>40 40<br>Plan Target Plan Target<br>30 30<br>20 20<br>2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030<br>2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030<br><!-- End of picture text --> 19
investment share in the Baseline Scenario, the investment share under Participation Scenario also reaches unfeasible levels soon enough and crosses the 65 percent mark in 2024. These results suggest that targeting sustainable GDP growth rates in the 7 – 8 percent range via boosting investment without TFP growth is bound to result in disappointment.

Like in the previous section, the quantitative findings here too inform that high TFP growth is essential if high levels of GDP growth are to be achieved, as TFP growth keeps required investment within feasible limits. The required investment share of GDP is close to the planned investment share when TFP grows by 1.5 percent each year. In fact, barring the last plan year the planned investment share exceeds or remains close to the required investment share. The growth of required investment share is muted in presence of TFP growth compared to the earlier two scenarios as TFP growth keeps capital to output ratio low thereby maintaining the productivity of expanding capital stock. However, sustaining 8 percent growth for a long period of time may still prove challenging as required investment share crosses 60 percent of GDP and reaches almost 50 percent of GDP under High Growth Scenarios I and II respectively.

# **3.3 Growth Led by External Sector**

In the model, the external sector plays no role in generating growth. This happens because the investment rate is fed exogenously into the model which does not respond to changes in the external sector. A shortcoming of this approach is that it is not possible to analyze growth that may be derived through foreign investment and external borrowing. To overcome this challenge, investment is made endogenous so that investment depends on national savings and funding from external sources. This is done using two simple external sector conditions.

The first external constraint requires that investment �� is the excess of national savings �� over the current account balance ���� : Equation (10) suggests that investment can be greater than national savings if the economy is able to run a current account deficit. The current account balance can be further decomposed as the acquisition of net foreign assets ���� less the incurrence of net foreign liabilities ���� : For simplicity, it is assumed that there are no changes in the stock of net foreign assets �Δ���� �0� . The change in net foreign liabilities equals the flow of foreign direct investment ���� augmented by the accumulation of the external debt during the period. Incorporating these in the previous equation gives: 20
Substituting the value of ���� from equation (11) in equation (10) and dividing both sides by �� yields the relationship between investment, national savings and the external sector in terms of share of GDP: The above equation captures the fact that investment can be boosted via three channels – increase in national savings, increase in foreign direct investment and increase in external debt.

The time paths of national savings, foreign direct investment and external debt are taken from the 7<sup>th</sup> Five Year Plan targets which are summarized below:

- Starting from 29.0 percent in 2015, savings to GDP rises to 31.9 percent by 2020

- Starting from 0.9 percent in 2015, FDI to GDP rises to 3.0 percent by 2020

- Starting from 25.1 percent in 2015, external debt to GDP rises to 37.4 percent by 2020

All the above variables are assumed to remain at the 2020 level from that year onward. Like in the previous section, four alternative growth scenarios are considered – Baseline, Participation and High Growth Scenarios I and II.

The following figures below show the GDP growth paths under different scenarios when investment responds to the external sector. The behavior of growth paths under various scenarios is very similar to the behavior seen earlier in section 3.1. An aspect of difference is the sudden jump in growth rate in 2017 which was absent in the previous case. This happens because the GDP growth during 2016 is a function of investment made in the previous year which is the same across the two exercises. Investment becomes responsive to the external sector beginning 2016 which has a one period delayed impact on growth which shows as the initial bump.

Under the Baseline Scenario, the GDP growth rate crosses the 6 percent mark in two intermediate Plan Years and averages 5.7 percent during the entire Plan Period. The growth rate starts declining past 2021 and remains just above 4 percent by 2030. As expected, the growth rate under Participation Scenario is higher compared to the Baseline Scenario and exceeds it by around 1 percentage point during each of the Plan Years. The growth rate declines by about 80 basis points in 2021 as growth in participation rate comes to an end. The growth rate continues to decline gradually and is just 10 basis points above the growth rate under Baseline Scenario in 2030. With an annual TFP growth rate of 1 percent, the GDP growth rate breaches the 8 percent mark in 2017 and averages just below 8 percent during 2016 – 2020. The GDP growth rate declines past 2020 as female labor force participation rate stabilizes. Yet, the growth rate remains above 6.5 percent for many periods. The implied growth rate is above the plan target when TFP grows by 1.5 percent per year. The average annual growth rate under High Growth II Scenario during the plan period outpaces the average annual plan growth rate 21
by more than 1 percentage point during most of the Plan Years. The growth rate remains above the 7 percent mark till 2026 and does not fall below 6.5 percent even after 15 years.

<!-- Start of picture text --> 10 Real GDP Growth (%) 10 Real GDP Growth (%)<br>Baseline Participation<br>9 9<br>8 Plan Target 8 Plan Target<br>7 7<br>6 6<br>5 5<br>4 4<br>3 3<br>2 2<br>10 Real GDP Growth (%) 10 Real GDP Growth (%)<br>High Growth<br>9 9<br>8 Plan Target 8 Plan Target<br>7 7<br>High Growth II<br>6 6<br>5 5<br>4 4<br>3 High Growth I 3<br>2 2<br>2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030<br>2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030<br><!-- End of picture text --> The implied investment share of GDP obtained using equation (12) is higher than the investment shares used in section 3.1. While the national savings as a share of GDP is lower than used the investment share even under the assumption that <u>public capital is perfectly</u>

||**Average**|**Annual Real GDP Gro**|**wth(%)**|
|---|---|---|---|
|**Scenario**|**2016 – 2020**|**2021 – 2025**|**2026 – 2030**|
|Baseline|5.70|5.26|4.31|
|Participation|6.76|5.46|4.44|
|High Growth I|7.98|6.90|5.98|
|High Growth II|8.59|7.63|6.77|
|**7**<sup>**th**</sup>**Five Year Plan Target**|**7.44**|‐|‐|

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efficient ���1� , this is more than offset by the FDI assumed to flow in each year. With an expanding external debt to GDP ratio, the implied investment share becomes even larger compared to the assumed path of investment share in section 3.1. This implies that the obtained growth path for a particular scenario will be higher compared to the corresponding scenario in which the investment is independent of changes in the external sector. This can also be seen by comparing the five year average rates shown in table below to the corresponding table presented in section 3.1.

In summary, all exercises underline the importance of a sustained high TFP growth in attaining a sustained high GDP growth. An investment‐led strategy by itself will not be able to deliver high growth for many years as without other factors driving growth, a resulting increase in capital‐to‐output ratio will keep chipping at the growth impact of investment. Given the importance of TFP growth, it is essential to identify factors that can generate high TFP growth growing forward. In the next section, I examine the quantitative impact of one such factor – more efficient allocation of existing resources across sectors.<sup>8</sup>

# **4. TFP Growth and Resource Allocation across Sectors**

Average labor productivity in agriculture is less than one‐fourth compared to average labor productivity in both industry and services. While the employment share of agriculture has shrunk by around 6.5 percentage points during the last 15 years, the country still employs 44 percent of its workforce in the relatively unproductive agricultural sector. The huge gaps in productivity across sectors are symptoms of misallocation of resources and economic growth can be achieved simply by moving resources out of agriculture to the other sectors.

While there are large gaps in average productivity, allocative efficiency requires a convergence in marginal productivity across sectors. Assuming Cobb‐Douglas production technologies at sector level together with perfect competition in factor markets, the measurement of marginal productivity reduces to adjusting the average products of a sector with the sector‐specific labor share of income. The table below shows the marginal productivity in industry and services relative to agriculture for Bangladesh which have been computed using labor shares of income at sector level from the GTAP database.

||**Margin**<br>|**al Productivity of La**<br>|**bor Relative to Agr **<br>|**iculture**<br>|
|---|---|---|---|---|
||**2000**|**2005**|**2010**|**2015**|
|Industry|4.38|4.41|4.19|4.32|
|Services|7.93|9.68|11.20|11.56|

> 8 Please see appendix A.2 for a brief discussion on factors that are important in driving TFP growth. This discussion is a summary of the survey on productivity by Syverson (2011). The interested reader should read the paper as the discussion here highlights only some of the important factors that can lead to productivity growth and is in no way provides a comprehensive listing of such factors.

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While there has been little change in marginal gaps in industry relative to agriculture since 2000, the productivity gap between services and agriculture has been on the rise. This is a direct consequence of the fact that the services share of value added has expanded without a corresponding increase in services share of employment. In fact, the services sector has lost a percentage point of representation in the aggregate employment.

To quantify the impact of reallocation of resources on economic growth, I apply the Sinha (2016) model of resource allocation in which productivity gaps arise as a result of asymmetrical taxes/distortions across sectors. The distortions in the model are a stylized approach to capture the effects of a host of frictions that restrict movement of resources across sectors. The distortions disappear if there are no frictions to movement of resources across sectors. To the extent that these distortions are positive for a particular sector when measured relative to agriculture, they imply a barrier to movement of resources out of agriculture and vice versa. The figure below plots these taxes for industry and services relative to agriculture. The trend in distortions captures the trend in marginal productivity gaps seen in the previous table.

<!-- Start of picture text --> 12<br>Services<br>10<br>8<br>6<br>4<br>Industry<br>2<br>0<br>2000 2005 2010 2015<br>Taxes Relative to Agriculture<br><!-- End of picture text --> In order to quantify the gains from a better resource allocation, I perform a simple counterfactual exercise. I ask how much of economic growth can be achieved by Bangladesh if the present level of distortions in the country are changed to what is observed in peer countries.<sup>9</sup> The following table reports the counterfactual growth in real GDP per capita together with distortions that deliver this growth. Real GDP per capita will more than double if the distortions in the country are reduced to the levels observed in China. On the other hand, real GDP per capita has the potential to increase by about 20 percent if distortions equal what is observed in India which has similar level of distortions in industry but much lower distortions in services.

> 9 The estimates of distortions for peer countries have been taken from Sinha (2016).

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Deis PB, Dé IP, Déi.1 = De — (PB; — IP) Yaa ~~Peta~~ <u>;</u> _ ~~<u>Pe_Ye</u>~~ <u>(</u> ~~<u>PBt_1Pe)\¥t</u> Ye~~ Ye+1 (149,00 ¢41)(1+9n,t41) PB, = (TAX, + NTAX,) — (CE, + If) + IP; TAX, NTAX, CE, If
assumptions on government operations and using growth rates from the model, the government debt to GDP path can be obtained by employing equation (13).

The simulations in section 3.1 outline the various growth scenarios for the economy. Under the Baseline Scenario, the annual GDP growth rate for the next 15 years varies in the range of 4 – 5 percent whereas under the most optimistic High Growth Scenario II the annual GDP growth rate varies in the range of 6.5 – 8.5 range. An interesting question in this regard is that whether such huge variation in growth rates spell remarkably different implications with regards to government debt position or not. To make quantitative progress on this front, the time path of government operations need to be fed into equations (13) and (14). In spirit of previous sections, the 7<sup>th</sup> Five Year Plan projections for government operations are used till 2020 after which the variables are assumed to remain at the level targeted in 2020. The assumptions on government operations are summarized below:<sup>10</sup>

- Starting from 9.3 percent in 2015, tax revenue reaches 14.1 percent of GDP by 2020

- Starting from 1.5 percent in 2015, non‐tax revenue reaches 2.0 percent of GDP by 2020

- Starting from 10.5 percent in 2015, current expenditures reaches 13.9 percent of GDP by 2020

- Starting from 2.0 percent in 2015, interest payment reaches 2.5 percent of GDP by 2020

- Starting from 6.9 percent in 2015, government capital expenditure reaches 7.8 percent of GDP by 2020<sup>11</sup>

The analysis of fiscal policy is carried out for the scenarios listed in section 3.1. Note that in all the scenarios aggregate investment remained the same, while the effective investment differed depending on the efficiency of public capital. The following figure plots the time path of government debt to GDP ratio for the different scenarios. Government debt to GDP ratio rises steadily over time as growth rate of GDP outpaces growth rate of government debt. The <!-- Start of picture text --> Government Debt to GDP (%)<br>130<br>110<br>90<br>70<br>50<br>30<br>Baseline E + P HG I HG II<br>2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030<br><!-- End of picture text --> 10 Intermediate year values for all variables correspond to what has been targeted in the Seventh Five Year Plan. 11 This is consistent with the inputs provided in section 3.1.

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debt ratio rises slower across different scenarios as the growth rate of GDP increases. Under the High Growth Scenarios II that features a 1.5 percent annual increase of TFP, the debt ratio rises slowest and reaches just above 63 percent by 2030. In contrast, the debt ratio rises fastest under the Baseline scenario and closes on the 80 percent mark by 2030. Yet, the government debt situation remains sustainable across all scenarios.

The discussion above suggests that the sustainability of government debt is a foregone conclusion as it remains sustainable even if the economy experiences tepid growth going forward. However, such a conclusion overlooks the fact that the debt situation is closely tied to government operations and is not only determined by economic growth. To test whether the debt sustainability faces risks if the underlying conditions of government operations are not met, I conduct a simple counterfactual. Specifically, I analyze the risks of government not meeting the tax revenue targets as laid out in the Five Year Plan with regards to the debt situation. Keeping all else the same, I assume that the tax revenue to GDP ratio fails to improve going forward and stays at 9.3 percent. The figure below illustrates the sharp contrast to the findings above. Like the figure before, the government debt to GDP ratio is increasing under each scenario but is rising at a much faster rate. The government debt surpasses GDP by 2030 even under the most optimistic High Growth II scenario and lies just below 125 percent of GDP under the Baseline scenario.

<!-- Start of picture text --> Government Debt to GDP (%)<br>130<br>110<br>90<br>70<br>50<br>30<br>Baseline E + P HG I HG II<br>2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030<br><!-- End of picture text --> The debt ratio reaches alarming levels if the revenue targets are not met. Such high debt ratios might bring sustainability of government debt under serious threat. The exercise shows that the government debt situation is sensitive to government operations and that meeting tax revenue targets is essential in keeping the government debt to GDP ratio in check. The government debt sustainability will face additional risk if the government overshoots its expenditure without making much progress on the revenue front.

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# **6. Conclusion**

Bangladesh has achieved robust economic growth for the last ten years with real GDP growing by more than 6 percent on average each year. The magnitude of GDP growth has come a long way from the 4 percent average annual growth rate of the late 1970s. The economic growth has also coincided with other favorable development outcomes like poverty reduction, literacy growth, etc. However, the more important question going forward is whether the country can maintain the high levels of growth seen in the last decade and if possible accelerate the growth rate. To help make progress in quantifying the long‐term growth prospects of the country, a simple growth model is developed. The model is calibrated to match key moments of the Bangladesh economy and the calibrated model is then used to analyze various growth scenarios.

The main finding of the analysis is that for Bangladesh to sustain a high real GDP growth rate, it is essential that the country focus on reforms that drive TFP growth. Even if the country manages to meet the levels of investment as outlined in the Seventh Five Year Plan, the country will fail to maintain the GDP growth rates achieved in the past decade without corresponding support from TFP growth. This also means that attaining high GDP growth in absence of growth in TFP will require investments that are much higher than planned levels and surpass realistic thresholds very soon.

An important factor that can provide a modest but meaningful contribution to economic growth in the medium term is the growth in female labor force participation. The country has made significant progress with regards to female labor force participation but there is still a massive scope for improvement. An 11 percentage point increase in the female labor force participation rate spread over the next 5 years can add more than 1 percentage point to GDP growth on average each year.

The model is also used to gain insights on government debt sustainability given different growth scenarios. The analysis highlights the significance of meeting revenue targets considering the expansion in expenditures. While the government debt for Bangladesh stands at a benign level, it has the potential to rise to cross the level of the country’s GDP in the next 15 years if the revenue targets are not met. The sustainability of government debt will come under additional pressure if the actual expenditure overshoots the already increasing planned expenditure.

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