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Transforming the Philippine Economy: "Walking on Two Legs"

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This paper analyzes the long-term growth of the Philippine economy through the lens of structural transformation to clarify the root causes of the country's lagged growth performance in the regional context.

• http://hdl.handle.net/11540/2047

With a strong recovery from the global crisis, the Philippines’ policy focus will shift again to a long-term development agenda. Despite favorable initial conditions, the Philippines’ long-term growth performance has been disappointing. Over the decades, the economy has suffered from high unemployment, slow poverty reduction, and stagnant investment.

Why could the Philippines not enjoy high growth as its neighbors? What are the main causes of its chronic problems of unemployment, poverty, and underinvestment? This paper argues that the Philippines’ poor growth performance is to be attributed to low productivity growth due to slow industrialization, especially in manufacturing. The chronic problems of high unemployment, slow poverty reduction, and low investment are reflections of slow industrialization. Initial success in electronics had enabled the economy to accumulate capabilities for productive diversification. However, incentives to utilize the accumulated capabilities have been weakened by persistent underprovision of basic infrastructure and weak business and investment climate.

The paper also analyzes the growing services sector, in particular the booming business process outsourcing industry, in terms of its impact on job creation. The key conclusion is that, instead of “leapfrogging” over industrialization, the Philippines needs to “walk on two legs,” to develop both industry and services, to generate job opportunities for the growing working-age population.

• Introduction-The Philippines' Development Puzzle
• Structural Transformation-Aggregate Productivity Growth
• Structural Transformation-Evolution of the Product Space
• Service-Led Growth-Is the BPO Industry the Savior?
• Concluding Remarks
• Selected References

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• Published: 04 April 2022

Economic losses from COVID-19 cases in the Philippines: a dynamic model of health and economic policy trade-offs

• Elvira P. de Lara-Tuprio 1 ,
• Maria Regina Justina E. Estuar 2 ,
• Joselito T. Sescon 3 ,
• Cymon Kayle Lubangco   ORCID: orcid.org/0000-0002-1292-4687 3 ,
• Rolly Czar Joseph T. Castillo 3 ,
• Timothy Robin Y. Teng 1 ,
• Lenard Paulo V. Tamayo 2 ,
• Jay Michael R. Macalalag 4 &
• Gerome M. Vedeja 3  

Humanities and Social Sciences Communications volume  9 , Article number:  111 ( 2022 ) Cite this article

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The COVID-19 pandemic forced governments globally to impose lockdown measures and mobility restrictions to curb the transmission of the virus. As economies slowly reopen, governments face a trade-off between implementing economic recovery and health policy measures to control the spread of the virus and to ensure it will not overwhelm the health system. We developed a mathematical model that measures the economic losses due to the spread of the disease and due to different lockdown policies. This is done by extending the subnational SEIR model to include two differential equations that capture economic losses due to COVID-19 infection and due to the lockdown measures imposed by the Philippine government. We then proceed to assess the trade-off policy space between health and economic measures faced by the Philippine government. The study simulates the cumulative economic losses for 3 months in 8 scenarios across 5 regions in the country, including the National Capital Region (NCR), to capture the trade-off mechanism. These scenarios present the various combinations of either retaining or easing lockdown policies in these regions. Per region, the trade-off policy space was assessed through minimising the 3-month cumulative economic losses subject to the constraint that the average health-care utilisation rate (HCUR) consistently falls below 70%, which is the threshold set by the government before declaring that the health system capacity is at high risk. The study finds that in NCR, a policy trade-off exists where the minimum cumulative economic losses comprise 10.66% of its Gross Regional Domestic Product. Meanwhile, for regions that are non-adjacent to NCR, a policy that hinges on trade-off analysis does not apply. Nevertheless, for all simulated regions, it is recommended to improve and expand the capacity of the health system to broaden the policy space for the government in easing lockdown measures.

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Introduction.

The Philippine population of 110 million comprises a relatively young population. On May 22, 2021, the number of confirmed COVID-19 cases reported in the country is 1,171,403 with 55,531 active cases, 1,096,109 who recovered, and 19,763 who died. As a consequence of the pandemic, the real gross domestic product (GDP) contracted by 9.6% year-on-year in 2020—the sharpest decline since the Philippine Statistical Agency (PSA) started collecting data on annual growth rates in 1946 (Bangko Sentral ng Pilipinas, 2021 ). The strictest lockdown imposed from March to April 2020 had the most severe repercussions to the economy, but restrictions soon after have generally eased on economic activities all over the country. However, schools at all levels remain closed and minimum restrictions are still imposed in business operations particularly in customer accommodation capacity in service establishments.

The government is poised for a calibrated reopening of business, mass transportation, and the relaxation of age group restrictions. The government expects a strong recovery before the end of 2021, when enough vaccines have been rolled out against COVID-19. However, the economic recovery plan and growth targets at the end of the year are put in doubt with the first quarter of 2021 growth rate of GDP at -4.2%. This is exacerbated by the surge of cases in March 2021 that took the National Capital Region (NCR) and contiguous provinces by surprise, straining the hospital bed capacity of the region beyond its limits. The government had to reinforce stricter lockdown measures and curfew hours to stem the rapid spread of the virus. The country’s economic development authority proposes to ensure hospitals have enough capacity to allow the resumption of social and economic activities (National Economic and Development Authority, 2020 ). This is justified by pointing out that the majority of COVID-19 cases are mild and asymptomatic.

Efforts in monitoring and mitigating the spread of COVID-19 requires understanding the behaviour of the disease through the development of localised disease models operationalized as an ICT tool accessible to policymakers. FASSSTER is a scenario-based disease surveillance and modelling platform designed to accommodate multiple sources of data as input allowing for a variety of disease models and analytics to generate meaningful information to its stakeholders (FASSSTER, 2020 ). FASSSTER’s module on COVID-19 currently provides information and forecasts from national down to city/municipality level that are used for decision-making by individual local government units (LGUs) and also by key government agencies in charge of the pandemic response.

In this paper, we develop a mathematical model that measures the economic losses due to the spread of the disease and due to different lockdown policies to contain the disease. This is done by extending the FASSSTER subnational Susceptible-Exposed-Infectious-Recovered (SEIR) model to include two differential equations that capture economic losses due to COVID-19 infection and due to the lockdown measures imposed by the Philippine government. We then proceed to assess the trade-off policy space faced by the Philippine government given the policy that health-care utilisation rate must not be more than 70%, which is the threshold set by the government before declaring that the health system capacity is at high risk.

We simulate the cumulative economic losses for 3 months in 8 scenarios across 5 regions in the country, including the National Capital Region (NCR) to capture the trade-off mechanism. These 8 scenarios present the various combinations of either retaining or easing lockdown policies in these regions. Per region, the trade-off policy space was assessed through minimising the 3-month cumulative economic losses subject to the constraint that the average health-care utilisation rate (HCUR) consistently falls below 70%. The study finds that in NCR, a policy trade-off exists where the minimum economic losses below the 70% average HCUR comprise 10.66% of its Gross Regional Domestic Product. Meanwhile, for regions that are non-adjacent to NCR, a policy that hinges on trade-off analysis does not apply. Nevertheless, for all simulated regions, it is recommended to improve and expand the capacity of the health system to broaden the policy space for the government in easing lockdown measures.

The sections of the paper proceed as follows: the first section reviews the literature, the second section explains the FASSSTER SEIR model, the third section discusses the economic dynamic model, the fourth section specifically explains the parameters used in the economic model, the fifth section briefly lays out the policy trade-off model, the sixth discusses the methods used in implementing the model, the seventh section presents the results of the simulations, the eighth section discusses and interprets the results, and the final section presents the conclusion.

Review of related literature

Overview of the economic shocks of pandemics.

The onslaught of the Coronavirus Disease 2019 (COVID-19) pandemic since 2020 has disrupted lifestyles and livelihoods as governments restrict mobility and economic activity in their respective countries. Unfortunately, this caused a –3.36% decline in the 2020 global economy (World Bank, 2022 ), which will have pushed 71 million people into extreme poverty (World Bank, 2020 ; 2021 ).

As an economic phenomenon, pandemics may be classified under the typologies of disaster economics. Particularly, a pandemic’s impacts may be classified according to the following (Benson and Clay, 2004 ; Noy et al., 2020 ; Keogh-Brown et al., 2010 ; 2020 ; McKibbin and Fernando, 2020 ; Verikios et al., 2012 ): (a) direct impacts, where pandemics cause direct labour supply shocks due to mortality and infection; (b) indirect impacts on productivity, firm revenue, household income, and other welfare effects, and; (c) macroeconomic impacts of a pandemic.

For most pandemic scenarios, social distancing and various forms of lockdowns imposed by countries around the world had led to substantial disruptions in the supply-side of the economy with mandatory business closures (Maital and Barzani, 2020 ; Keogh-Brown et al., 2010 ). Social distancing will have contracted labour supply as well, thus contributing to contractions in the macroeconomy (Geard et al., 2020 ; Keogh-Brown et al., 2010 ). Thus, in general, the literature points to a pandemic’s impacts on the supply- and demand-side, as well as the displacement of labour supply; thus, resulting in lower incomes (Genoni et al., 2020 ; Hupkau et al., 2020 ; United Nations Development Programme, 2021 ). Often, these shocks result from the lockdown measures; thus, a case of a trade-off condition between economic losses and the number of COVID-19 casualties.

Static simulations for the economic impacts of a pandemic

The typologies above are evident in the analyses and simulations on welfare and macroeconomic losses related to a pandemic. For instance, computable general equilibrium (CGE) and microsimulation analyses for the 2009 H1N1 pandemic and the COVID-19 pandemic showed increases in inequities, welfare losses, and macroeconomic losses due to lockdown and public prevention strategies (Cereda et al., 2020 ; Keogh-Brown et al., 2020 ; Keogh-Brown et al., 2010 ). Public prevention-related labour losses also comprised at most 25% of the losses in GDP in contrast with health-related losses, which comprised only at most 17% of the losses in GDP.

Amidst the COVID-19 pandemic in Ghana, Amewu et al. ( 2020 ) find in a social accounting matrix-based analysis that the industry and services sectors will have declined by 26.8% and 33.1%, respectively. Other studies investigate the effects of the pandemic on other severely hit sectors such as the tourism sector. Pham et al. ( 2021 ) note that a reduction in tourism demand in Australia will have caused a reduction in income of tourism labourers. Meanwhile, in a static CGE-microsimulation model by Laborde, Martin, and Vos ( 2021 ), they show that as the global GDP will have contracted by 5% following the reduction in labour supply, this will have increased global poverty by 20%, global rural poverty by 15%, poverty in sub-Saharan Africa by 23%, and in South Asia by 15%.

However, due to the static nature of these analyses, the clear trade-off between economic and health costs under various lockdown scenarios is a policy message that remains unexplored, as the simulations above only explicitly tackle a pandemic’s macroeconomic effects. This gap is mostly due to these studies’ usage of static SAM- and CGE-based analyses.

Dynamic simulations for the economic impacts of a pandemic

An obvious advantage of dynamic models over static approaches in estimating the economic losses from the pandemic is the capacity to provide forward-looking insights that have practical use in policymaking. Epidemiological models based on systems of differential equations explicitly model disease spread and recovery as movements of population across different compartments. These compartmental models are useful in forecasting the number of infected individuals, critically ill patients, death toll, among others, and thus are valuable in determining the appropriate intervention to control epidemics.

To date, the Susceptible-Infectious-Recovered (SIR) and SEIR models are among the most popular compartmental models used to study the spread of diseases. In recent years, COVID-19 has become an important subject of more recent mathematical modelling studies. Many of these studies deal with both application and refinement of both SIR and SEIR to allow scenario-building, conduct evaluation of containment measures, and improve forecasts. These include the integration of geographical heterogeneities, the differentiation between isolated and non-isolated cases, and the integration of interventions such as reducing contact rate and isolation of active cases (Anand et al., 2020 ; Chen et al., 2020 ; Hou et al., 2020 ; Peng et al., 2020 ; Reno et al., 2020 ).

Typical epidemiological models may provide insight on the optimal lockdown measure to reduce the transmissibility of a virus. However, there is a need to derive calculations on economic impacts from the COVID-19 case projections to arrive at a conclusion on the optimal frontier from the trade-off between health and economic losses. In Goldsztejn, Schwartzman and Nehorai ( 2020 ), an economic model that measures lost economic productivity due to the pandemic, disease containment measures and economic policies is integrated into an SEIR model. The hybrid model generates important insight on the trade-offs between short-term economic gains in terms of productivity, and the continuous spread of the disease, which in turn informs policymakers on the appropriate containment policies to be implemented.

This approach was further improved by solving an optimal control of multiple group SIR model to find the best way to implement a lockdown (Acemoglu et al., 2020 ). Noting the trade-offs between economic outcomes and spread of disease implied in lockdown policies, Acemoglu et al. ( 2020 ) find that targeted lockdown yields the best result in terms of economic losses and saving lives. However, Acemoglu et al. ( 2020 ) only determine the optimal lockdown policy and their trade-off analysis through COVID-associated fatalities. Kashyap et al. ( 2020 ) note that hospitalisations may be better indicators for lockdown and, as a corollary, reopening policies.

Gaps in the literature

With the recency of the pandemic, there is an increasing but limited scholarship in terms of jointly analysing the losses brought about by the pandemic on health and the economy. On top of this, the literature clearly has gaps in terms of having a trade-off model that captures the context of low- and middle-income countries. Devising a trade-off model for said countries is an imperative given the structural and capability differences of these countries from developed ones in terms of responding to the pandemic. Furthermore, the literature has not explicitly looked into the trade-off between economic losses and health-care system capacities, both at a national and a subnational level.

With this, the paper aims to fill these gaps with the following. Firstly, we extend FASSSTER’s subnational SEIR model to capture the associated economic losses given various lockdown scenarios at a regional level. Then, we construct an optimal policy decision trade-off between the health system and the economy in the Philippines’ case at a regional level. From there, we analyse the policy implications across the different regions given the results of the simulations.

The FASSSTER SEIR model

The FASSSTER model for COVID-19 uses a compartmental model to describe the dynamics of disease transmission in a community, and it is expressed as a system of ordinary differential equations (Estadilla et al., 2021 ):

where β  =  β 0 (1– λ ), \(\alpha _a = \frac{c}{\tau }\) , \(\alpha _s = \frac{{1 - c}}{\tau }\) , and N ( t ) =  S ( t ) =  E ( t ) +  I a ( t ) +  I s ( t ) +  C ( t ) +  R ( t ).

The six compartments used to divide the entire population, namely, susceptible ( S ), exposed ( E ), infectious but asymptomatic ( I a ), infectious and symptomatic ( I s ), confirmed ( C ), and recovered ( R ), indicate the status of the individuals in relation to the disease. Compartment S consists of individuals who have not been infected with COVID-19 but may acquire the disease once exposed to infectious individuals. Compartment E consists of individuals who have been infected, but not yet capable of transmitting the disease to others. The infectious members of the population are split into two compartments, I a and I s , based on the presence of disease symptoms. These individuals may eventually transition to compartment C once they have been detected, in which case they will be quarantined and receive treatment. The individuals in the C compartment are commonly referred to as active cases. Finally, recovered individuals who have tested negative or have undergone the required number of days in isolation will move out to the R compartment. Given that there had only been rare instances of reinfection (Gousseff et al., 2020 ), the FASSSTER model assumes that recovered individuals have developed immunity from the disease. A description of the model parameters can be found in Supplementary Table S1 .

The model has several nonnegative parameters that govern the movement of individuals along the different compartments. The parameter β represents the effective transmission rate, and it is expressed as a product of the disease transmission rate β 0 and reduction factor 1 −  λ . The rate β 0 is derived from an assumed reproduction number R 0 , which varies depending on the region. The parameter λ reflects the effect of mobility restrictions such as lockdowns and compliance of the members of the population to minimum health standards (such as social distancing, wearing of face masks etc.). In addition, the parameter ψ captures the relative infectiousness of asymptomatic individuals in relation to those who exhibit symptoms.

The incubation period τ and fraction of asymptomatic cases c are used to derive the transfer rates α α and α s from the exposed compartment to I a and I s compartments, respectively. Among those who are infectious and asymptomatic, a portion of them is considered pre-symptomatic, and hence will eventually develop symptoms of the disease; this is reflected in the parameter ω. The respective detection rates δ a and δ s of asymptomatic and symptomatic infectious individuals indicate the movement from the undetected infectious compartment to the confirmed compartment. These parameters capture the entire health system capacity to prevent-detect-isolate-treat-reintegrate (PDITR) COVID-19 cases; hence, they will henceforth be referred to as HSC parameters. The recoveries of infectious asymptomatic individuals and among the active cases occur at the corresponding rates θ and r . Death rates due to the disease, on the other hand, are given by ∈ I and ∈ T for the infectious symptomatic and confirmed cases, respectively.

Aside from the aforementioned parameters, the model also utilises parameters not associated with the COVID-19 disease, such as the recruitment rate A into the susceptible population. This parameter represents the birth rate of the population and is assumed to be constant. In addition, a natural death rate per unit of time is applied to all compartments in the model, incorporating the effect of non-COVID-19 related deaths in the entire population.

Economic dynamic model

The trade-off model aims to account for the incurred economic losses following the rise and fall of the number of COVID-19 cases in the country and the implementation of various lockdown measures. The model variables are estimated per day based on the SEIR model estimate of daily cases and are defined as follows. Let Y E ( t ) be the economic loss due to COVID-19 infections (hospitalisation, isolation, and death of infected individuals) and Y E ( t ) be the economic loss due to the implemented lockdown at time t . The dynamics of each economic variable through time is described by an ordinary differential equation. Since each equation depends only on the values of the state variables of the epidemiological model, then it is possible to obtain a closed form solution.

Economic loss due to COVID-19 infections (hospitalisation, isolation, and health)

The economic loss due to hospitalisation, isolation, and death Y E is described by the following differential equation:

where z  = annual gross value added of each worker (assumed constant for all future years and for all ages), w  = daily gross value added, ι i  = % population with ages 0–14 ( i  = 1), and labour force with ages 15–34 ( i  = 2), 35–49 ( i  = 3) and 50–64 ( i  = 4), s r  = social discount rate, κ  = employed to population ratio, T i  = average remaining productive years for people in age bracket i , i  = 1, 2, 3, 4, and T 5  = average age of deaths from 0–14 years old age group. Note that the above formulation assumes that the young population 0–14 years old will start working at age 15, and that they will work for T 1 −15 years.

Solving Eq. ( 7 ), we obtain for t  ≥ 0,

In this equation, the terms on the right-hand side are labelled as (A), (B), and (C). Term (A) is the present value of all future gross value added of 0–14 years old who died due to COVID-19 at time t . Similarly, term (B) is the present value of all future gross value added of people in the labour force who died due to COVID-19 at time t . Term (C) represents the total gross value added lost at time t due to sickness and isolation.

The discounting factors and the population age group shares in (A) and (B) can be simplified further into K 1 and K 2 , where \(K_1 = \iota _1\left( {\frac{{\left( {s_r + 1} \right)^{T_1 + T_5 - 13} - \left( {s_r + 1} \right)}}{{s_r\left( {s_r + 1} \right)^{T_1 + 1}}}} \right)\) and \(K_2 = \mathop {\sum}\nolimits_{i = 2}^4 {\iota _i\left( {\frac{{\left( {s_r + 1} \right)^{T_i + 2} - \left( {s_r + 1} \right)}}{{s_r\left( {s_r + 1} \right)^{T_i + 1}}}} \right)}\) . By letting L 1  = z( K 1  +  K 2 ) ∈ I  +  κw (1 –  ∈ I ) and L 2  = z( K 1  +  K 2 ) ∈ T  +  κw (1 –  ∈ T ), we have:

Economic losses due to lockdown policies

Equation ( 7 ) measures the losses due mainly to sickness and death from COVID-19. The values depend on the number of detected and undetected infected individuals, C and I s . The other losses sustained by the other part of the population are due to their inability to earn because of lockdown policies. This is what the next variable Y L represents, whose dynamics is given by the differential equation

where φ  = the displacement rate, and κ and w are as defined previously.

Solving the differential equation, then

Note that [ S ( t ) +  E ( t ) +  I a ( t ) +  R ( t )] is the rest of the population at time t , i.e., other than the active and infectious symptomatic cases. Multiplying this by κ and the displacement rate φ yields the number of employed people in this population who are displaced due to the lockdown policy. Thus, κwφ [ S ( t ) +  E ( t ) +  I a ( t ) +  R ( t )] is the total foregone income due to the lockdown policy.

Economic model parameters

The values of the parameters were derived from a variety of sources. The parameters for employment and gross value added were computed based on the data from the Philippine Statistics Authority ( 2021 , 2020 , 2019a , 2019b ), the Department of Health’s Epidemiology Bureau (DOH-EB) ( 2020 ), the Department of Trade and Industry (DTI) ( 2020a , 2020b ) and the National Economic Development Authority (NEDA) ( 2016 ) (See Supplementary Tables S2 and S3 for the summary of economic parameters).

Parameters determined from related literature

We used the number of deaths from the data of the DOH-EB ( 2020 ) to disaggregate the long-term economic costs of the COVID-related deaths into age groups. Specifically, the COVID-related deaths were divided according to the following age groups: (a) below 15 years old, (b) 15 to 34 years old, (c) 35 to 49 years old, and (d) 50 to 64 years old. The average remaining years for these groups were computed directly from the average age of death of the respective cluster. Finally, we used the social discount rate as determined by NEDA ( 2016 ) to get the present value of the stream of foregone incomes of those who died from the disease.

Parameters estimated from local data

The foregone value added due to labour displacement was estimated as the amount due to workers in a geographic area who were unable to work as a result of strict lockdown measures. It was expected to contribute to the total value added in a given year if the area they reside or work in has not been locked down.

The employed to population ratio κ i for each region i was computed as

where e i was total employment in region i , and Pi was the total population in the region. Both e i and Pi were obtained from the quarterly labour force survey and the census, respectively (Philippine Statistics Authority, 2020 , 2019a , 2019b ).

The annual gross value added per worker z i for region i was computed as

where g ji was the share of sector j in total gross value added of region i , GVA ji was the gross value added of sector j in region i (Philippine Statistics Authority, 2021 ), and e ji was the number of employed persons in sector j of region i . If individuals worked for an average of 22.5 days for each month for 12 months in a year, then the daily gross value added per worker in region i was given by

Apart from this, labour displacement rates were calculated at regional level. The rates are differentiated by economic reopening scenarios from March 2020 to September 2020, from October 2020 to February 2021, and from March 2021 onwards (Department of Trade and Industry, 2020a , 2020b , 2021 ). These were used to simulate the graduate reopening of the economy. From the country’s labour force survey, each representative observation j in a region i is designated with a numerical value in accordance with the percentage operating capacity of the sector where j works in. Given the probability weights p ji , the displacement rate φ i for region i was calculated by

where x ji served as the variable representing the maximum operating capacity designated for j ’s sector of work.

Policy trade-off model

The trade-off between economic losses and health measures gives the optimal policy subject to a socially determined constraint. From the literature, it was pointed out that the optimal policy option would be what minimises total economic losses subject to the number of deaths at a given time (Acemoglu et al., 2020 ). However, for the Philippines’ case, lockdown restrictions are decided based on the intensive care unit and health-care utilisation rate (HCUR). The health system is said to reach its critical levels if the HCUR breaches 70% of the total available bed capacity in intensive care units. Once breached, policymakers would opt to implement stricter quarantine measures.

Given these, a policy mix of various quarantine restrictions may be chosen for as long as it provides the lowest amount of economic losses subject to the constraint that the HCUR threshold is not breached. Since economic losses are adequately captured by the sum of infection-related and lockdown-related losses, Y E ( t ) +  Y L ( t ), then policy option must satisfy the constrained minimisation below:

where the objective function is evaluated from the initial time value t 0 to T .

The COVID-19 case information data including the date, location transformed into the Philippine Standard Geographic Code (PSGC), case count, and date reported were used as input to the model. Imputation using predictive mean matching uses the mice package in the R programming language. It was performed to address data gaps including the date of onset, date of specimen collection, date of admission, date of result, and date of recovery. Population data was obtained from the country’s Census of Population and Housing of 2015. The scripts to implement the FASSSTER SEIR model were developed using core packages in R including optimParallel for parameter estimation and deSolve for solving the ordinary differential equations. The output of the model is fitted to historical data by finding the best value of the parameter lambda using the L-BFGS-B method under the optim function and the MSE as measure of fitness (Byrd et al., 1995 ). The best value of lambda is obtained by performing parameter fitting with several bootstraps for each region, having at least 50 iterations until a correlation threshold of at least 90% is achieved. The output generated from the code execution contains values of the different compartments at each point in time. From these, the economic variables Y E ( t ) and Y L ( t ) were evaluated using the formulas in Eq. ( 7 ) and ( 8 ) in their simplified forms, and the parameter and displacement rate values corresponding to the implemented lockdown scenario (Fig. 1 ).

The different population states are represented by the compartments labelled as susceptible (S), exposed (E), infectious but asymptomatic ( I a ), infectious and symptomatic ( I s ), confirmed (C), and recovered (R).

We simulate the economic losses and health-care utilisation capacity (HCUR) for the National Capital Region (NCR), Ilocos Region, Western Visayas, Soccsksargen, and for the Davao Region by implementing various combinations of lockdown restrictions for three months to capture one quarter of economic losses for these regions. The National Capital Region accounts for about half of the Philippines’ gross domestic product, while the inclusion of other regions aim to represent the various areas of the country. The policy easing simulations use the four lockdown policies that the Philippines uses, as seen in Table 1 .

Simulations for the National Capital Region

Table 2 shows the sequence of lockdown measures implemented for the NCR. Each lockdown measure is assumed to be implemented for one month. Two sets of simulations are implemented for the region. The first set assumes a health systems capacity (HSC) for the region at 17.99% (A), while the second is at 21.93% (B). A higher HSC means an improvement in testing and isolation strategies for the regions of concern.

From the sequence of lockdown measures in Table 2 , Fig. 2 shows the plot of the average HCUR as well as the corresponding total economic losses for the two sets of simulations for one quarter. For the scenario at 17.99% HSC (A), the highest loss is recorded at 16.58% of the annual gross regional domestic product (GRDP) while the lowest loss is at 12.19% of its GRDP. Lower average HCUR corresponds to more stringent scenarios starting with Scenario 1. Furthermore, under the scenarios with 21.93% HSC (B), losses and average HCUR are generally lower. Scenarios 1 to 4 from this set lie below the 70% threshold of the HCUR, with the lowest economic loss simulated to be at 9.11% of the GRDP.

These include the set of trade-off decisions under a health system capacity equal to 17.99%, and another set equal to 21.93% (Source of basic data: Authors’ calculations).

Overall, the trend below shows a parabolic shape. The trend begins with an initial decrease in economic losses as restrictions loosen, but this comes at the expense of increasing HCUR. This is then followed by an increasing trend in losses as restrictions are further loosened. Notably, the subsequent marginal increases in losses in the simulation with 21.93% HSC are smaller relative to the marginal increases under the 17.99% HSC.

Simulations for the Regions Outside of NCR

Table 2 also shows the lockdown sequence for the Ilocos, Western Visayas, Soccsksargen, and Davao regions. The sequence begins with Level III only. Meanwhile, the lowest lockdown measure simulated for the regions is Level I. Two sets of simulations with differing health system capacities for each scenario are done as well.

With this lockdown sequence, Fig. 3 shows the panel of scatter plot between the average HCUR and total economic losses as percentage of the respective GRDP, with both parameters covering one quarter. Similar to the case of the NCR, the average HCUR for the simulations with higher health system capacity (B) is lower than the simulations with lower health system capacity (A). However, unlike in NCR, the regions’ simulations do not exhibit a parabolic shape.

These include trade-offs for a Ilocos Region, b Western Visayas Region, c Soccsksargen Region, and d Davao Region (Source of basic data: Authors’ calculations).

Discussion and interpretation

The hypothetical simulations above clearly capture the losses associated with the pandemic and the corresponding lockdown interventions by the Philippine government. The trend of the simulations clearly shows the differences in the policy considerations for the National Capital Region (NCR) and the four other regions outside of NCR. Specifically, the parabolic trend of the former suggests an optimal strategy that can be attained through a trade-off policy even with the absence of any constraint in finding the said optimal strategy. This trend is borne from the countervailing effects between the economic losses due to COVID-19 infection ( Y E ) and the losses from the lockdown measures ( Y L ) implemented for the region. Specifically, Fig. 4(a), (b) show the composition of economic losses across all scenarios for the NCR simulation under a lower and higher health system capacity (HSC), respectively.

These include losses under a HSC = 17.99% and b HSC = 21.93% in the National Capital Region (Source of basic data: Authors’ calculations).

In both panels of Fig. 4 , as quarantine measures loosen, economic losses from infections ( Y E ) tend to increase while the converse holds for economic losses due to quarantine restrictions ( Y L ). The results are intuitive as loosening restrictions may lead to increased mobility, and therefore increased exposure and infections from the virus. In fact, economic losses from infections ( Y E ) take up about half of the economic losses for the region in Scenario 7A, Fig. 4(a) .

While the same trends can be observed for the scenarios with higher HSC at 21.93%, the economic losses from infections ( Y E ) do not overtake the losses simulated from lockdown restrictions ( Y L ) as seen in Fig. 4(b) . This may explain the slower upward trend of economic losses in Fig. 2 at HSC = 21.93%.

The output of the simulation for the Davao region shows that the economic losses from COVID-19 infections ( Y E ) remain low even as the lockdown restrictions ease down. At the same time, economic losses from lockdown restrictions ( Y L ) show a steady decline with less stringent lockdown measures. Overall, the region experiences a decreasing trend in total economic losses even as the least stringent lockdown measure is implemented for a longer period. This pattern is similar with the regions of Ilocos, Western Visayas, and Soccsksarkgen.

The results of the simulations from Figs. 2 and 3 also demonstrate differing levels of economic losses and health-care utilisation between the two sets of scenarios for NCR and the four other regions. Clearly, lower economic losses and health-care utilisation rates were recorded for the scenarios with higher HSC. Specifically, lower total economic losses can be attributed to a slower marginal increase in losses from infections ( Y E ) as seen in Fig. 4(b) . Thus, even while easing restrictions, economic losses may be tempered with an improvement in the health system.

With the above analysis, the policy trade-off as a constrained minimisation problem of economic losses subject to HCUR above appears to apply in NCR but not in regions outside of NCR. The latter is better off in enhancing prevention, detection, isolation, treatment, and reintegration (PDITR) strategy combined with targeted small area lockdowns, if necessary, without risking any increases in economic losses. But, in all scenarios and anywhere, the enhancement of the HSC through improved PDITR strategies remains vital to avoid having to deal with local infection surges and outbreaks. This also avoids forcing local authorities in a policy bind between health and economic measures to implement. Enhancing PDITR in congested urban centres (i.e., NCR) is difficult especially with the surge in new daily cases. People are forced to defy social distance rules and other minimum health standards in public transportation and in their workplaces that help spread the virus.

We extended the FASSSTER subnational SEIR model to include two differential equations that capture economic losses due to COVID-19 infection and due to the lockdown measures, respectively. The extended model aims to account for the incurred economic losses following the rise and fall of the number of active COVID-19 cases in the country and the implementation of various lockdown measures. In simulating eight different scenarios in each of the five selected regions in the country, we found a tight policy choice in the case of the National Capital Region (NCR) but not in the cases of four other regions far from NCR. This clearly demonstrates the difficult policy decision in the case of NCR in minimising economic losses given the constraint of its intensive care unit (ICU) bed capacity.

On the other hand, the regions far from the NCR have wider policy space towards economic reopening and recovery. However, in all scenarios, the primary significance of improving the health system capacity (HSC) to detect and control the spread of the disease remains in order to widen the trade-off policy space between public health and economic measures.

The policy trade-off simulation results imply different policy approaches in each region. This is also to consider the archipelagic nature of the country and the simultaneous concentration of economic output and COVID-19 cases in NCR and contiguous provinces compared to the rest of the country. Each local region in the country merits exploration of different policy combinations in economic and health measures depending on the number of active COVID-19 cases, strategic importance of economic activities and output specific in the area, the geographic spread of the local population and their places of work, and considering local health system capacities. However, we would like to caution that the actual number of cases could diverge from the results of our simulations. This is because the parameters of the model must be updated regularly driven generally by the behaviour of the population and the likely presence of variants of COVID-19. Given the constant variability of COVID-19 data, we recommend a shorter period of model projections from one to two months at the most.

In summary, this paper showed how mathematical modelling can be used to inform policymakers on the economic impact of lockdown policies and make decisions among the available policy options, taking into consideration the economic and health trade-offs of these policies. The proposed methodology provides a tool for enhanced policy decisions in other countries during the COVID-19 pandemic or similar circumstances in the future.

Data availability

The raw datasets used in this study are publicly available at the Department of Health COVID-19 Tracker Website: https://doh.gov.ph/covid19tracker . Datasets will be made available upon request after completing request form and signing non-disclosure agreement. Code and scripts will be made available upon request after completing request form and signing non-disclosure agreement.

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Acknowledgements

We thank Dr. Geoffrey M. Ducanes, Associate Professor, Ateneo de Manila University Department of Economics, for giving us valuable comments in the course of developing the economic model, and Mr. Jerome Patrick D. Cruz, current Ph.D. student, Massachusetts Institute of Technology, for initiating and leading the economic team in FASSSTER in the beginning of the project for their pitches in improving the model. We also thank Mr. John Carlo Pangyarihan for typesetting the manuscript. The project is supported by the Philippine Council for Health Research and Development, United Nations Development Programme and the Epidemiology Bureau of the Department of Health.

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All authors contributed to the study conception and design. Model conceptualization, data collection and analysis were performed by EPdL-T, MRJEE, JTS, CKL, CJTC, TRYT, LPT, JMRM, and GMV. All authors commented on previous versions of the manuscript, and read and approved the final manuscript.

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de Lara-Tuprio, E.P., Estuar, M.R.J.E., Sescon, J.T. et al. Economic losses from COVID-19 cases in the Philippines: a dynamic model of health and economic policy trade-offs. Humanit Soc Sci Commun 9 , 111 (2022). https://doi.org/10.1057/s41599-022-01125-4

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DOI : https://doi.org/10.1057/s41599-022-01125-4

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This paper, which will be released as the lead chapter of the 2022–2023 PIDS Economic Policy Monitor , examines the economic performance of the Philippines for 2022 and the first half of 2023. It presents conditions shaping the global and regional outlook, projections on growth and consumer prices, and prospects coming into 2024. Carried by post-pandemic momentum but moderated by continued headwinds, the economy grew by 7.6 percent in 2022. For 2023, GDP growth is expected to weaken to 5.2 percent, and inflation is estimated to average at about 6 percent. As for 2024, growth is anticipated to register between 5.5 to 6 percent, while inflation is expected to fall to the center of the target band. These projections consider the steady stream of income from abroad, an improved jobs picture, benign financial conditions, a less restrictive public budget, and a possible resurgence and/or rising business expectations in some sectors. On top of the issues listed in the previous edition, the current one draws attention to risks related to inflation, the country’s fiscal position, and the newly created national investment fund.

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The Philippine economy under the pandemic: From Asian tiger to sick man again?

Subscribe to the center for asia policy studies bulletin, ronald u. mendoza ronald u. mendoza dean and professor, ateneo school of government - ateneo de manila university.

August 2, 2021

In 2019, the Philippines was one of the fastest growing economies in the world. It finally shed its “sick man of Asia” reputation obtained during the economic collapse towards the end of the Ferdinand Marcos regime in the mid-1980s. After decades of painstaking reform — not to mention paying back debts incurred under the dictatorship — the country’s economic renaissance took root in the decade prior to the pandemic. Posting over 6 percent average annual growth between 2010 and 2019 (computed from the Philippine Statistics Authority data on GDP growth rates at constant 2018 prices), the Philippines was touted as the next Asian tiger economy .

That was prior to COVID-19.

The rude awakening from the pandemic was that a services- and remittances-led growth model doesn’t do too well in a global disease outbreak. The Philippines’ economic growth faltered in 2020 — entering negative territory for the first time since 1999 — and the country experienced one of the deepest contractions in the Association of Southeast Asian Nations (ASEAN) that year (Figure 1).

Figure 1: GDP growth for selected ASEAN countries

And while the government forecasts a slight rebound in 2021, some analysts are concerned over an uncertain and weak recovery, due to the country’s protracted lockdown and inability to shift to a more efficient containment strategy. The Philippines has relied instead on draconian mobility restrictions across large sections of the country’s key cities and growth hubs every time a COVID-19 surge threatens to overwhelm the country’s health system.

What went wrong?

How does one of the fastest growing economies in Asia falter? It would be too simplistic to blame this all on the pandemic.

First, the Philippines’ economic model itself appears more vulnerable to disease outbreak. It is built around the mobility of people, yet tourism, services, and remittances-fed growth are all vulnerable to pandemic-induced lockdowns and consumer confidence decline. International travel plunged, tourism came to a grinding halt, and domestic lockdowns and mobility restrictions crippled the retail sector, restaurants, and hospitality industry. Fortunately, the country’s business process outsourcing (BPO) sector is demonstrating some resilience — yet its main markets have been hit heavily by the pandemic, forcing the sector to rapidly upskill and adjust to emerging opportunities under the new normal.

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Second, pandemic handling was also problematic. Lockdown is useful if it buys a country time to strengthen health systems and test-trace-treat systems. These are the building blocks of more efficient containment of the disease. However, if a country fails to strengthen these systems, then it squanders the time that lockdown affords it. This seems to be the case for the Philippines, which made global headlines for implementing one of the world’s longest lockdowns during the pandemic, yet failed to flatten its COVID-19 curve.

At the time of writing, the Philippines is again headed for another hard lockdown and it is still trying to graduate to a more efficient containment strategy amidst rising concerns over the delta variant which has spread across Southeast Asia . It seems stuck with on-again, off-again lockdowns, which are severely damaging to the economy, and will likely create negative expectations for future COVID-19 surges (Figure 2).

Figure 2 clarifies how the Philippine government resorted to stricter lockdowns to temper each surge in COVID-19 in the country so far.

Figure 2: Community quarantine regimes during the COVID-19 pandemic, Philippine National Capital Region (NCR ), March 2020 to June 2021

If the delta variant and other possible variants are near-term threats, then the lack of efficient containment can be expected to force the country back to draconian mobility restrictions as a last resort. Meanwhile, only two months of social transfers ( ayuda ) were provided by the central government during 16 months of lockdown by mid-2021. All this puts more pressure on an already weary population reeling from deep recession, job displacement, and long-term risks on human development . Low social transfers support in the midst of joblessness and rising hunger is also likely to weaken compliance with mobility restriction policies.

Third, the Philippines suffered from delays in its vaccination rollout which was initially hobbled by implementation and supply issues, and later affected by lingering vaccine hesitancy . These are all likely to delay recovery in the Philippines.

By now there are many clear lessons both from the Philippine experience and from emerging international best practices. In order to mount a more successful economic recovery, the Philippines must address the following key policy issues:

• Build a more efficient containment strategy particularly against the threat of possible new variants principally by strengthening the test-trace-treat system. Based on lessons from other countries, test-trace-treat systems usually also involve comprehensive mass-testing strategies to better inform both the public and private sectors on the true state of infections among the population. In addition, integrated mobility databases (not fragmented city-based ones) also capacitate more effective and timely tracing. This kind of detailed and timely data allows for government and the private sector to better coordinate on nuanced containment strategies that target areas and communities that need help due to outbreak risk. And unlike a generalized lockdown, this targeted and data-informed strategy could allow other parts of the economy to remain more open than otherwise.
• Strengthen the sufficiency and transparency of direct social protection in order to give immediate relief to poor and low-income households already severely impacted by the mishandling of the pandemic. This requires a rebalancing of the budget in favor of education, health, and social protection spending, in lieu of an over-emphasis on build-build-build infrastructure projects. This is also an opportunity to enhance the social protection system to create a safety net and concurrent database that covers not just the poor but also the vulnerable low- and lower-middle- income population. The chief concern here would be to introduce social protection innovations that prevent middle income Filipinos from sliding into poverty during a pandemic or other crisis.
• Ramp-up vaccination to cover at least 70 percent of the population as soon as possible, and enlist the further support of the private sector and civil society in order to keep improving vaccine rollout. An effective communications campaign needs to be launched to counteract vaccine hesitancy, building on trustworthy institutions (like academia, the Catholic Church, civil society and certain private sector partners) in order to better protect the population against the threat of delta or another variant affecting the Philippines. It will also help if parts of government could stop the politically-motivated fearmongering on vaccines, as had occurred with the dengue fever vaccine, Dengvaxia, which continues to sow doubts and fears among parts of the population .
• Create a build-back-better strategy anchored on universal and inclusive healthcare. Among other things, such a strategy should a) acknowledge the critically important role of the private sector and civil society in pandemic response and healthcare sector cooperation, and b) underpin pandemic response around lasting investments in institutions and technology that enhance contact tracing (e-platforms), testing (labs), and universal healthcare with lower out-of-pocket costs and higher inclusivity. The latter requires a more inclusive, well-funded, and better-governed health insurance system.

As much of ASEAN reels from the spread of the delta variant, it is critical that the Philippines takes these steps to help allay concerns over the country’s preparedness to handle new variants emerging, while also recalibrating expectations in favor of resuscitating its economy. Only then can the Philippines avoid becoming the sick man of Asia again, and return to the rapid and steady growth of the pre-pandemic decade.

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Unemployment, Labor Laws, and Economic Policies in the Philippines

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Unemployment and underemployment are the Philippines’ most important problems and the key indicators of the weaknesses of the economy. Today, around 4 million workers (about 12% of the labor force) are unemployed and another 5 million (around 17% of those employed) are underemployed. This Reserve Army of workers is a reflection of what happens in the economy, particularly because of its incapacity to provide jobs (especially in the formal sector) to its growing labor force. The social costs of this mass unemployment range from income losses to severe social and psychological problems resulting from not having a job and feeling insecure about the future. Overall, it causes a massive social inefficiency.

The authors thank participants at the workshop, Employment Creation, Labor Markets, and Growth in the Philippines (19 May 2005, Manila) for their comments and suggestions on an earlier draft of the chapter. They also thank Rana Hasan for useful discussions on labor market issues.

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Felipe, J., Lanzona, L. (2006). Unemployment, Labor Laws, and Economic Policies in the Philippines. In: Felipe, J., Hasan, R. (eds) Labor Markets in Asia. Palgrave Macmillan, London. https://doi.org/10.1057/9780230627383_7

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A new vision for the Philippine economy after Covid-19

The Philippines | Economy

The Philippines is one of the fastest-growing economies of the past decade, averaging 6.4% growth per year in 2010-19. Indeed, an expanding and youthful population, combined with reforms and an ambitious infrastructure programme, have made it an enticing investment destination. Nevertheless, as is often the case in emerging markets, challenges regarding inequality – particularly the distribution of wealth and services – remain barriers to growth. The Covid-19 pandemic tested the country’s resilience in 2020, impacting major sectors. However, the government mobilised to support vulnerable industries with two major stimulus bills, which aim to create jobs and sustain growth into 2021.

The Philippines has shifted from an agricultural to a broadly services-focused economy. According to the central bank, Bangko Sentral ng Pilipinas (BSP), in 2019 agriculture, forestry and fisheries made up 9.2% of GDP, behind industry (30.2%) and services (60.6%). Services overtook industry as the leading contributor to GDP in the 1980s and accounted for almost 60% of total employment by 2019 – highlighting the growing importance of IT-business process outsourcing (IT-BPO). In addition to IT-BPO, export services, including those delivered by overseas Filipino workers (OFWs), play a significant role. Remittances from OFWs reached a record $33.5bn in 2019, representing 9.3% of GDP.

Industry accounted for 19.1% of workers in 2019 and is centred around manufacturing and agri-business. The development of a number of special economic zones should help bolster industrial growth in the years to come. The agriculture sector, which has shrunk considerably since 1980, has nevertheless been highlighted as a strategic sector for economic recovery amid Covid-19: the government identified food security as a primary concern. The sector employed 22.9% of workers in 2019, and its main products include rice, coconuts, maize, sugarcane, bananas, pineapples and mangoes.

Government Oversight

The Philippines’ primary socio-economic and policy planning body is the National Economic and Development Authority (NEDA). President Rodrigo Duterte has been head of the Cabinet since 2016, serving a six-year term, and also chairs the NEDA board. Karl Kendrick Chua occupies the positions of vice-chairperson and acting socio-economic secretary. The board includes the heads of various government departments, the governor of the BSP and the chairperson of the Mindanao Development Authority.

Development Plans

The Philippine Development Plan (PDP) 2017-22 is the medium-term economic blueprint for inclusive growth. Its primary aims include tackling poverty and regional growth disparities, and transforming the nation into a globally competitive knowledge economy. Its three pillars are building trust and transparency between government and society; reducing inequality and increasing opportunities; and accelerating growth through innovation and human-capital development. Prior to the pandemic, goals included achieving upper-middle-income status, reducing the poverty rate to 14%, and lowering rural poverty from 30% in 2015 to 20% by 2022. As of mid-2020 revisions to PDP targets were under discussion in light of the pandemic; however, poverty-reduction goals look set to remain a priority. In July 2020 Chua stated that “the immediate objective under the PDP will now focus on a healthy and more resilient Philippines”. Furthermore, in October 2020 NEDA and the World Bank published a report underscoring the importance of digitalisation and digital adoption, and decreasing the digital divide to meet economic aspirations.

Longer-term planning is anchored in the AmBisyon Natin 2040 vision, formulated in 2016, which aims to eradicate poverty and create a middle-income country. This would require tripling GDP per capita from $2892 to $9350 by 2040, and growing the economy by an average of 6.5% per year from 2018. Priority sectors highlighted under the plan include manufacturing, health, agriculture and financial services. The plan, which is being implemented by NEDA, is aligned with the administration’s 10-point socio-economic agenda, which includes tax reforms and improvements to the ease of doing business, and the UN 2030 Sustainability Development Goals. In July 2020, at an online World Bank forum, Chua said the country had achieved seven of the 10 points on the socio-economic agenda, highlighting the passage of the Tax Reform for Acceleration and Inclusion (TRAIN) among other reforms.

2019 Performance

Average economic growth of 6.4% in 2010-19 was up from 4.5% over the previous 10 years. Indeed, despite subdued global growth and uncertainty, GDP growth of 6% in 2019 – while slightly down from 6.3% in 2018 – marked the Philippines as one of the fastest-growing nations in the world. These fundamentals were reflected on the World Bank’s ease of doing business index in 2020: the Philippines rose 29 places to rank 95th out of 190. The bank highlighted improvements in starting a business, dealing with construction permits and protecting minority investors.

Economic expansion in 2019 was driven by the services sector, which grew by 7.5% to total P11.7trn ($232.7bn), according to the BSP. This was propelled by growth in numerous subsectors, notably public administration, defence and social security, which grew by 13.4%, and financial and insurance activities, up 11.9%. The IT-BPO segment grew by 7.1%, recording $26.3bn in revenue, according to figures from the IT and Business Process Association of the Philippines.

Meanwhile, industry growth eased from 7.3% to 4.7%, to reach P5.8trn ($115.4bn). Expansion was driven by construction (7.8%); electricity, steam, water and waste management (6.6%); mining and quarrying (3.6%); and manufacturing (3.2%). Construction’s growth rate, while high, was down from the 14.3% growth seen the previous year due to the delayed passage of the 2019 budget and the subsequent ban on public works during the mid-term election in May 2019. Likewise, manufacturing grew slower than the 5.1% expansion seen in 2018, marking the weakest growth for the subsector since 2009 (see Industry and Agri-business chapter).

Agriculture posted growth of 1.2% in 2019, up from 1.1% in 2018, to contribute P1.9trn ($37.8bn). Performance was attributed to key agricultural products such as maize, which expanded by 3.3%; mangoes (4.3%); and poultry and eggs (5.8%). However, contractions in segments such as sugarcane (-8.9%), palay (unhusked rice) (-5.9%) and bananas (-2.1%) weighed on growth, prompting the government to rethink agricultural programmes and projects that favour resilient crops.

Impact of Covid-19

The first case of Covid-19 on Philippine soil was confirmed in January 2020, and strict quarantine measures were imposed to varying degrees from mid-March onwards. As a result, the economy shrunk by 0.7% year-on-year (y-o-y) in the first quarter, 16.5% in the second and 11.5% in the third – a stark contrast to the 5.4% growth seen in the second quarter of 2019. This was driven by weaker remittances from OFWs, which were down 9.3% y-o-y in the second quarter, and slower growth in investment, exports and tourism earnings. According the IMF’s October 2020 “World Economic Outlook”, real GDP is forecast to contract by 8.3% in 2020 – the largest drop in Southeast Asia. This projected recession is deeper than the IMF’s June forecast of -3.6%, as the country continued to face one of the highest confirmed case rates in ASEAN, with over 435,000 cases as of December 2020.

Services, meanwhile, contracted by 15.8% y-o-y in the second quarter, compared to growth of 7.5% one year earlier. Given its sizeable share of GDP, the segment’s contraction translated into a 9.7-percentage-point drop in overall GDP, primarily due to stay-at-home measures and the grounding of land, sea and air travel. However, certain segments posted positive growth, including financial and insurance activities (6.8%) and ICT (6.6%), with e-commerce platforms moving customers to online transactions and e-payments (see Digital Economy chapter). Industry, for its part, contracted by 22.9% y-o-y, compared to growth of 2.5% in the same quarter of 2019. The decline shaved 6.9 percentage points off overall GDP, with construction and manufacturing contracting by 33.5% and 21.3%, respectively, due to restrictions on non-essential services under enhanced community quarantine (ECQ) – the country’s strictest lockdown category. However, as with services, certain segments grew during this period: pharmaceutical products and preparations, for example, expanded by 7.7%, following 27.3% y-o-y growth in the first quarter. Lastly, the agriculture sector, driven mainly by higher palay, maize, sugar cane and rubber production, grew by 1.6% y-o-y. The sector will continue to play an important role in economic recovery due to its connection to food security and poverty reduction.

Government Response

In response to the pandemic, and following a sharp increase in community transmission, ECQ was enforced across the most populous island of Luzon from March 16. The lockdown prompted the government to pass the Bayanihan to Heal as One (Bayanihan 1) Act on March 25, 2020, which granted President Duterte emergency powers to address the crisis. Among the mitigation efforts was a P595.6bn ($11.8bn) fiscal package for vulnerable individuals and groups, which included P205bn ($4.1bn) in cash aid for 18m low-income households; some P57bn ($1.1bn) in social-protection measures for workers; over P58bn ($1.2bn) for the medical response; and a P120bn ($2.4bn) credit guarantee for small and medium-sized enterprises (SMEs) and support for agriculture.

The Bayanihan to Recover as One Act (Bayanihan 2) was subsequently signed into law on September 11 to extend emergency relief, expand health care, and help businesses and OFWs. The P165.5bn ($3.3bn) stimulus included P140bn ($2.8bn) for hard-hit industries and a standby fund of P25.5bn ($507.2m) for the government to spend until the 2021 budget takes effect (see analysis). “Under Bayanihan 2 we allotted P820m ($16.3bn) to boost assistance to OFWs. OFW remittances will always be a significant factor in our post-pandemic recovery, as these will support consumption, savings and investment,” President Duterte told OBG. “We have therefore launched programmes such as the BaLinkBayan Portal and the Overseas Filipinos Remittances for Development project, which aim to harness remittances for investment and capital mobilisation.”

Other legislative measures include the Corporate Recovery and Tax Incentives for Enterprises ( CREATE) bill, which includes gradually lowering corporate income tax from 30% to 20% by 2027, among other pro-business incentives, and is the second package of the Comprehensive Tax Reform Programme (CTRP). Now approved by both the House of Representatives and the Senate, it is set to be enacted before the end of 2020 (see analysis). In a similar vein, in August 2020 the Securities and Exchange Commission (SEC) issued a regulatory framework for the creation and operation of a new corporate debt vehicle intended to support medium and large firms dealing with liquidity issues. “In addition to CREATE and Bayanihan 2, the government has worked on corporate debt vehicle programmes that are attractive to local and foreign investors,” Jose Luis Gomez, president and CEO of RCBC Capital, told OBG.

Fiscal Policy

Government spending had been increasing in the years leading to 2020 due to major infrastructure upgrades called for under the PDP 2017-22. Full-year public expenditure amounted to a record P3.8trn ($75.6bn) in 2019, or 19.5% of GDP, up 11.4% on the previous year. According to the Department of Budget Management, the bulk of public spending went to infrastructure projects under the Build, Build, Build programme, which increased by 9.7% to P881.7bn ($17.5bn) in 2019. With regard to public sector inflows, tax revenue grew by 10.2% and non-tax revenue by 8.9%, leading to overall government revenue growth of 10.1%, totalling P3.1trn (P61.7bn). Overall, however, this amounted to a budget deficit of 3.2% of GDP, equivalent to 2018. Meanwhile, the government’s outstanding debt-to-GDP ratio fell from 41.9% in 2018 to 39.6% in 2019, the lowest since 1986. Tax reform under TRAIN contributed to overall state revenue and narrowed the fiscal gap, enabling the Philippines to enter 2020 in a relatively strong position, with a P4.1trn ($81.5bn) state budget – up 12% on the amount earmarked in 2019.

Government expenditure rose by 7% and 22.1% in the first and second quarters of 2020, respectively, due to the pandemic. Total expenditure equated to a deficit of P473.3bn ($9.4bn) in the second quarter, reversing the P47.6bn ($946.7m) surplus one year earlier and equivalent to 11.4% of GDP. On the income side, revenue stood at P690.2bn ($13.7bn), or 16.6% of GDP, down 17.7% y-o-y. Higher spending was attributed to Bayanihan 1 and measures to protect vulnerable industries. By the end of August the deficit had risen to P740.7bn ($14.7bn), state revenue was down 8.3% and spending had increased by a further 20.8%. However, while state revenue in January-August fell by 12.2% y-o-y, a combined P1.6trn ($31.8bn) was collected, exceeding the period’s adjusted target by 7.2%.

In October 2020 the House of Representatives approved the 2021 budget and the Senate gave its approval in late November. Set at P4.5trn ($89.5bn), the budget – which will undergo a final review in December – is 9.9% larger than in 2020 and equal to 21.8% of projected GDP for 2021. It includes P203.1bn ($4bn) for health care to address the pandemic and P1.1trn ($21.9bn) for infrastructure to kick-start the economy.

Monetary Policy

Headline inflation decreased from an average of 5.9% in 2018 to 2.5% in 2019 – which sits within the BSP’s target range of 3% plus or minus one percentage point – and was attributed to slower price increases for food and energy items. In turn, household spending grew by 5.9% in 2019, with food and non-alcoholic beverages up 5.1%, and housing, water, electricity, gas and other fuels rising by 6.3%. Over the course of 2019 the BSP cut the key policy rate by 75 basis points (bps) as inflation eased, bringing the overnight reverse repurchase rate to 4%. In addition, after a cumulative 200-bp cut to the banking reserve requirement ratio (RRR) in 2018, it made 400 bps of cut in 2019, bringing the rate to 14% (see Financial Services chapter). To soften the impact of Covid-19, the BSP cut the RRR by 200 bps in March 2020, releasing P200bn ($4bn) into the financial system, with a maximum of 400 bps in cuts authorised for the year. This followed a reduction in the key policy rate by 50 bps in March to 3.25%. In the second quarter of 2020 the bank reduced its key policy rate by a further 100 bps, bringing the overnight reverse repo rate to 2.25%, a historic low. In October 2020 the BSP decided to hold the rate at 2.25%. Headline inflation, meanwhile, eased to 2.4% in the second quarter, down from 2.7% in the first quarter of 2020.

Trade & Investment

Despite sluggish global growth and trade uncertainty arising from US-China tensions, the Philippines exported $70.3bn of goods in 2019, up from $69.3bn in 2018, according to the Philippine Statistics Authority (PSA). This narrowed the trade deficit from $43.5bn to $37.1bn, marking a shift away from the deficit pressure of construction materials imported for the Build, Build, Build programme. The top-three export destinations were the US, up 7.7% at $11.46bn; Japan (3%, $10.63bn); and China (9.2%, $9.63bn). The top-three export groups were electrical products, at $40bn, or 57% of the total; other manufactured goods ($4.2bn, 6%); and machinery and transport equipment ($2.8bn, 4%). Imports, meanwhile, totalled $107.4bn, down from $112.8bn in 2018. The top-three import markets were China, up 11.5% at $24.5bn; Japan (-6.4%, $10.1bn); and South Korea (-27.2%, $8.2bn). The top-three import groups were electronic products, at $28.1bn, or 26% of the total; mineral fuels, lubricants and related materials ($12.8bn, 12%); and transport equipment ($11bn, 10.2%). Foreign direct investment (FDI), however, dipped to $7.7bn in 2019, a four-year low. Despite marking a 21.3% drop, the total was nonetheless higher than the $6.8bn forecast. Stakeholders attributed uncertainty over the passage of CREATE as one reason for the subdued FDI inflows. While the delay from its first approval in September 2019 may have caused some investors to adopt a wait-and-see approach, there is optimism that the lower tax rates and incentives outlined in the act will boost investment appeal in the longer term – strengthening the Philippines’ bid to attract players seeking to diversify operations away from China.

International trade faced a challenging environment in 2020 as Covid-19 curtailed economic activity. The Philippines recorded steep contractions in both imports and exports in the first eight months of the year, according to the PSA. Export earnings totalled $39.3bn in January-August, a 16.6% y-o-y decrease. FDI inflows, meanwhile, were down 11% y-o-y in January-July, at $3.8bn, according to the BSP. On a positive note, however, FDI net inflows rose for the third consecutive month in July on the back of improving investor sentiment due in part to easing of containment measures.

Labour Market

The labour market, characterised by a young and English-speaking workforce, has long been attractive. Efforts are under way to unlock further potential, such as digitalisation initiatives to upskill the IT-BPO workforce and modernise agriculture via innovation. In 2019 the labour participation rate was 61.3%, with 42.4m employed. As a result of Covid-19 and related lockdowns, unemployment rose to 17.7% in April 2020 – and the labour participation rate dropped to 55.6%. Declines were seen across the main economic sectors: services registered a 22.8% decrease in employment; industry fell by 28.2%; and agriculture was down 9.5%. On a positive note, according to the PSA, things have improved somewhat, with an additional 7.5m employed in July compared to April. Gains were seen across virtually all regions and sectors. Notably, agriculture saw an increase of 2.1m due to higher output, and construction registered an additional 1.2m employees as construction activity resumed. The passage of Bayanihan 2 is expected to offset some employment losses through subsidies and cash relief for affected households and workers. Around 50,000 micro- and SMEs, for example, should benefit from a further P10bn ($198.9m) allocation under the stimulus.

While 2020 was a challenging period for the Philippine economy, the government is striving to turn the pandemic into opportunity. The signing of Bayanihan 1 and 2, the reopening of vital industries and the imminent passage of the CREATE bill should support recovery. While 2020 GDP is forecast to contract significantly, the Asian Development Bank expects a rebound in 2021, with GDP growth projected at 6.5%.

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Privacy Overview

Addressing Unemployment: A Critical Issue in the Philippine Economy

8 Pages Posted: 18 Mar 2024

Albert Castillo

World Citi Colleges - Quezon City - Graduate School Department; Rebtrade International Corporation

Marmelo V. Abante

World Citi Colleges - Quezon City - Graduate School Department

Florinda Vigonte

Date Written: February 19, 2024

This study provides an in-depth analysis of the unemployment issue in the Philippines. It explores the various factors contributing to unemployment, including macroeconomic conditions, labor market rigidities, and skill mismatches. The study also examines the impact of unemployment on economic development and social stability. Based on the findings, the study proposes a set of policy interventions aimed at promoting inclusive growth, enhancing the employability of the labor force, and addressing structural issues in the labor market. The recommendations are intended for policymakers, economists, researchers, students, educators, and scholars in the field. The study contributes to the broader goal of fostering sustainable economic development in the Philippines.

Keywords: unemployment, philippine economy, circular economy, government programs, PRISMA diagram, systematic review

JEL Classification: economy

Suggested Citation: Suggested Citation

Albert Castillo (Contact Author)

World citi colleges - quezon city - graduate school department ( email ).

Philippines

Rebtrade International Corporation ( email )

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What can significantly boost the Philippine economy?

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Using historical analysis and empirical evidence, DLSU School of Economics Distinguished Professor and Angelo King Institute of Economic and Business Studies Director Dr. Jesus Felipe offers a fresh outlook on the development of an innovative economy and the role of the government and private sector in shaping it.

With a 5.5% growth rate in 2023, the Philippines painted a steady recovery past the global pandemic. For this year, the government expects the economy to grow between 6% and 7% amid anticipated world economic slowdown.

While the expected growth rate is lower than the 6.5%-7.5% projection made last December, the government tries to be optimistic, with the country’s economic managers setting their goal for 2025: an upper middle-income status (which is at least USD 4,256 gross national income per capita). Government officials list the following to achieve the target: a low inflation, a labor force with access to more and better jobs, a stronger fiscal standing, and a dynamic and innovative economy.

But are these enough to allow the Philippines to be on par with its more developed Asian neighbors?

In order to answer this complex question, Dr. Jesus Felipe, Distinguished Professor of the De La Salle University School of Economics and director of the Angelo King Institute of Economic and Business Studies, traces the journey to innovation and industrialization. South Korea is a good case study of a country he considers the best example in the region.

“First, we expect at the School of Economics that growth in 2024 will be about 5.6%, significantly below the government’s expectations. Growth will pick in 2025 and 2026, when we expect it will reach 6.3 and 6.0%, respectively. We think this is the most the Philippine economy can grow today. It does not have the capacity to grow faster, much less for a long time,” Felipe shares.

On the broader question of what a successful nation like South Korea did back in the 1960s, President Park Chung Hee realized that industrialization through manufacturing was his country’s ticket out of poverty. “Manufacturing is a sector with special properties. Once you learn how to make certain products within the electronics cluster, for example, you develop some capabilities that you can redeploy to make many other products. The same thing happens when you make it into the automobile or chemical sectors. You create linkages with other sectors of the economy, and learn by doing, which increases your productivity and reduces your costs. All this is much harder in traditional agriculture and in many services—think of waiters in restaurants or sales personnel in department stores,” Felipe says.

“South Korea realized that the world is very large. It was producing manufacturing products, not just for the South Korean consumers but for the world,” he points out.

A second element of industrialization is the role of exports. South Korea’s rapid export expansion also began in the 1960s and this accelerated their process of development. Exports played two fundamental roles. First, it forced companies to compete with the world economy. This means that they had to become better as time passed by. That is, they had to compete not just in price but also, and more important in the long run, in terms of product quality and sophistication. Korean cars improved in quality very quickly. Second, a developing country needs to import all those goods that are necessary for its development, in particular capital goods (machinery) that help transform the economy. These goods have to be paid in a foreign currency, typically US dollars. These have to be earned via exports.

Felipe also notes that other countries like Japan, Taiwan, Singapore, China, and Vietnam, even with differing economies, have also applied the same model. “That’s the essence of what development is about—once you start manufacturing products, you move up the ladder. You start manufacturing and exporting very simple products, then you end up manufacturing very complex cars, machines, electronics, and chemical products.”

Unlike its neighbors, the Philippines followed a completely different economic path, relegating its manufacturing sector to a small sector, in particular from the employment side. Felipe notes: “Historically, we do not know of any nation that has attained high income per capita without developing a significant manufacturing sector. Where do you think innovation comes from? Manufacturing. You may have some type of innovation in the service sector but it is, one way or another, always linked to what you do in manufacturing.”

When asked about the chances of the Philippines to catch up in the industrialization train, Felipe says, “There are always opportunities out there in terms of niches. In the manufacturing sector, it is a big aggregate that, in reality, is thousands of products. And I’m familiar with manufacturing companies in the Philippines in most of the sectors, including chemicals. So, the challenge is how to multiply that experience in the next few years, in the next couple of decades, to be able to develop some niches where we may have opportunities.”

He adds that the key is for the Philippines to have very competitive, meaning productive, firms that will both produce for the domestic market and export and compete in the world economy.

Likewise, Felipe emphasizes the vital role of the government. “It is absolutely fundamental. Without a government directing the economy in the right direction, it is going to be very difficult for the economy to progress. The government must have a clear national vision and must work with the private sector, which is composed of thousands of firms. The government must indicate the overall direction.”

The thrust on industrialization should be at the center of the country’s policy agenda, he says, adding that the work needs strong collaboration between the private and public sectors, from academe to media to the general public.

“How do we become an industrial nation? How do we strengthen the niches that are going to help us?” He notes that for the country “to achieve higher wages and higher capita income, it needs to create a wide base of domestic industrial companies that produce the myriad of basic products across the whole manufacturing spectrum that support national development. This is something that everybody needs to be aware of.”

To make various stakeholders understand the state of the Philippine economy, Dr. Jesus Felipe and the DLSU School of Economics have initiated various seminar-lectures that feature international speakers and faculty researchers tackling topics such as short- and long-run growth, inflation, fiscal consolidation, investment, and economic structure.

Contact: Dr. Jesus Felipe | [email protected]

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The Balance Sheet Approach (BSA) is a presentation of the country’s sectoral accounts on a from whom-to-whom (WTW) basis using the aggregate balance sheet data of each sector of the economy.

International Investment Position

The International Investment Position (IIP) is a companion framework to the Balance of Payments (BOP) statistics. While the BOP is a statistical statement that records the country’s transactions or flows with the rest of the world for a given period, the IIP summarizes the country’s stock of financial claims on and financial liabilities to the rest of the world as of a specific reporting period.

Philippine Flow of Funds

The Philippine Flow of Funds presents the financial transactions of and among the different institutional sectors of the domestic economy, including the rest of the world. The report also shows which institutions are net lenders and net borrowers in the series of transactions.

Quarterly Report on Economic and Financial Development

The Quarterly Report on Economic and Financial Development is a quarterly report which outlines the major developments in the real, monetary and fiscal sectors of the Philippine economy.

Report on Regional Economic Developments

The Report on Regional Economic Developments in the Philippines tracks economic activities in the regions, focusing on the demand and supply conditions, price developments and monetary conditions, as well as the emerging outlook. Analysis of regional trends and developments supplements BSP’s analytical tools for monetary policy formulation and financial supervision. Qualitative and quantitative information used in the report are collected from primary and secondary sources and reflect the extensive information gathered by the BSP regional offices and branches.

Investor Relations Office Newsletter

The quarterly newsletter carries articles and information about the Philippine economy, including economic statistics, policy reforms, major infrastructure development projects, credit rating updates, investor relations activities, and outlook on the Philippine economy.

Macroprudential Policy Strategy Framework: The Case of the Philippines

The Macroprudential Policy Strategy Framework reflects the thinking of financial authorities, the institutional arrangements as well as the tools that will be used to sustain and enhance the health of the financial system. This health is specifically defined in terms of system's resilience against systemic risks.

Systemic Risk Crisis Management Framework

Full Report

Recent Trends in the Philippine Financial System

Report on Recent Trends in the Philippine Financial System, as of end-March 2024.

Philippine Financial Social Accounting Matrix

2017 Philippine Financial Social Accounting Matrix (PFSAM)

Press Release | Full Report

Sustainability Report

2023 Sustainability Report

National Strategy for Financial Inclusion 2022-2028

2022 NSFI Report

Financial Services Cyber Resilience Plan 2024-2029

2023 report on e-payment measurement.

The report on E-payments measurement is an annual report that features significant data and insights on the status of digital payments in the country.

Press Release | --> Full Report | Archives

Tweets from The Governor

B. statistical reports and publications, daily key statistical indicators report.

The daily key statistical indicators report contains data on selected domestic and foreign interest rates, commodity prices of sugar, coconut oil, gold and silver, and Peso-Dollar exchange rates.

Latest Data

Reference Exchange Rate Bulletin

The Reference Exchange Rate Bulletin contains the weighted average rates of selected currencies.

Selected Economic and Financial Indicators

The Selected Economic and Financial Indicators (SEFI) is a weekly compilation of various indicators on output, employment and wages, prices, money and interest rates, external indicators and public finance.

Monthly Selected Philippine Economic Indicators

The Monthly Selected Philippine Economic Indicators (SPEI) is a monthly compilation of various statistical tables on external accounts, financial system, fiscal, prices, and other real sector accounts.

Latest Release | Archives

Factbook: The Philippine Banking System

A two-volume compilation of various information and statistical data of the BSP Supervised Financial Institutions such as Physical Network and Directory, Aggregated Balance Sheet and Income Statement, Regional Distribution of Selected Accounts, individual Published Balance Sheet of Universal/Commercial/Thrift Banks and Summary Report on Compliance with Agri-Agra and MSME.

2021 Full Report Vol. 2 Full Report Vol. 2 --> | Archives

Annual Report Volume II - Statistical Bulletin

This publication contains statistical data relating to economic areas covering money, banking, credit and investment, public finance, foreign exchange transactions; balance of payments and external debt; production, construction and public utilities; and prices. The series presented in this report may be used as indicators of the impact of policies and measures adopted by the Monetary Board and in support of the analysis of the economic and financial developments discussed in the Annual Report text.

Residential Real Estate Price Index (RREPI)

The RREPI is a measure of the average price change of the different types of residential properties in the country over time.

Press Release | Archives

Commercial Property Price Index (CPPI)

The CPPI is a measure of the average price change of the different uses of commercial properties in the country over time.

Business Expectations Survey

The Business Expectations Survey (BES) is a nationwide quarterly survey of the Bangko Sentral ng Pilipinas (BSP) on business owners' or management's sentiment on their industry and the national economy for the current quarter, next quarter, and next 12 months.

Questionnaire

Consumer Expectations Survey Report

The Consumer Expectations Survey (CES) is a nationwide quarterly survey of the Bangko Sentral ng Pilipinas (BSP) on consumers’ sentiments, i.e., Philippine household sentiments, on family income, financial situation, and economic condition of the country for the current quarter, next quarter, and next 12 months.

Consumer Finance Survey

The Consumer Finance Survey (CFS) is a nationwide triennial survey of the Bangko Sentral ng Pilipinas (BSP) on the financial conditions of Filipino households, including their assets and debts, income and expenditures, as well as access to financial services.

Senior Bank Loan Officers' Survey

Report on the results of the quarterly Senior Bank Loan Officers' Survey conducted by the BSP to enhance its understanding of banks’ lending behavior, which is an important indicator of the strength of credit activity in the country.

Survey of IT-BPO Services Report

The report on the Survey of IT-BPO Services, formerly known as the Survey of IT and IT-Enabled Services, provides information on the economic contribution of IT and IT-Enabled services based on a survey conducted by the BSP. The survey covers member-firms of the different information and communication technology (ICT) associations and firms registered with attached agencies of the Department of Trade and Industry, namely, the Philippine Economic Zone Authority and the Board of Investments.

Coordinated Portfolio Investment Survey

The Coordinated Portfolio Investment Survey (CPIS) is a tool used to collect data on residents’ holdings of foreign-issued equities and long- and short-term debt securities semi-annually. The CPIS is a global undertaking spearheaded by the International Monetary Fund (IMF) in coordination with participating countries worldwide to improve statistics on holdings of external portfolio investment assets and promote international data comparability.

Philippine Banking Sector Outlook Survey

The Banking Sector Outlook Survey (BSOS) serves as a complementary tool in validating the assessments of banking supervisors.

Countryside Bank Survey

The 2022 Countryside Bank Survey Report.

D. RESEARCH AND STUDIES

Bsp working paper series.

The BSP Working Paper Series constitutes studies relevant to central banks, which are conducted by BSP researchers and occasionally, in collaboration with external contributors. The working papers are reviewed by the Editorial Committee, led by the Deputy Governor of the Monetary and Economics Sector.   Completed working papers are published annually for the purpose of soliciting comments and discussion for further refinements. The views and opinions expressed are those of the author(s) and do not necessarily reflect those of the Bangko Sentral ng Pilipinas. Authors keep the copyright and hence, improved versions of working papers may be submitted to peer-reviewed journals at any time.

BSP International Research Conference Volume

The BSP International Research Conference Volume is the compendium of all research papers presented during the BSP International Research Conference.

The BS Review serves primarily as a forum for presenting the research findings of BSP staff; includes analytical and policy-oriented research articles on various economic, financial and statistical issues of interest to the BSP.

BSP Economic Newsletter

The BSP Economic Newsletter aims to provide to the BSP community and the public a readily accessible, up-to-date, concise and reader-friendly compendium of studies on current economic and financial issues.

No One Left Behind: The Philippine Financial Inclusion Journey

Occasional papers.

Foreign exchange markets in Asia-Pacific prepared by the Study Group on FX Markets in Asia Pacific established by the Asian Consultative Council of the Bank for International Settlements (BIS), which was participated by the Department of Economic Research and Financial Markets

Capital flows, exchange rates and policy frameworks in emerging Asia: A report by a Working Group established by the Asian Consultative Council of the Bank for International Settlements 27 November 2020

Central Bank Digital Currency for the BSP Fundamentals and Strategies

BSP-UP Professorial Chair Lectures

The BSP-UP Professorial Chair Lecture Series is an annual event hosted by the Bangko Sentral ng Pilipinas (BSP) in cooperation with the University of the Philippines (UP). UP Professorial Chairholders are invited to give a lecture on their written research output at the BSP.

BSP International Research Fairs

BSP's International Research Fairs featuring top-caliber and rigorous research papers relevant to central banking in the Philippines and other emerging countries.

Disclaimer: No reproduction of the materials herewith are to be made without the consent and permission of the authors and speakers. Please kindly contact them personally for permission to quote, and make sure that any mention of the results and discussions in their study or presentation is credited to the author and his/ her research paper by making use of the publication web links, if available in the case of published research, or the link to the BSP International Research Fair folder and/or the author’s own webpage, in the case of research still in the pipeline for publication, where applicable.

BSP Discussion Papers

The papers present draft research output and are being disseminated for discussion purposes.

BSP International Research Conference

The BSP International Research Conference is a biennial event that engages central banks and leading experts from academia in the discussion of emerging and pressing policy issues. The 2021 conference marks the first time that the Bangko Sentral ng Pilipinas (BSP) is joined by the Reinventing Bretton Woods Committee (RBWC). The partnership could not have been more timely. The breadth and depth of the COVID-19 crisis have profound social, health, economic, and geopolitical ramifications. Central banks are confronted with multiple policy issues that may persist in the years to come and can, potentially, serve as fodder to future crises. .

3rd BSP International Research Fair

Disclaimer: No reproduction of the materials herewith are to be made without the consent and permission of the authors and speakers. Please kindly contact them personally for permission to quote, and make sure that any mention of the results and discussions in their study or presentation is credited to the author and his/her research paper by making use of the publication web links, if available in the case of published research, or the link to the BSP International Research Fair 2023 folder and/or the author’s own webpage, in the case of research still in the pipeline for publication, where applicable.

2nd BSP International Research Fair

Disclaimer: No reproduction of the materials herewith are to be made without the consent and permission of the authors and speakers. Please kindly contact them personally for permission to quote, and make sure that any mention of the results and discussions in their study or presentation is credited to the author and his/her research paper by making use of the publication web links, if available in the case of published research, or the link to the BSP International Research Fair 2022 folder and/or the author’s own webpage, in the case of research still in the pipeline for publication, where applicable.

Philippine Review of Economics

Strategies and initiatives on digital financial inclusion: lessons from experiences of apec economies, labor market implications of the covid-19 pandemic in the philippines, e. special publications, the story of philippine central banking: strength and stability at seventy, bsp unbound: central banking and the covid-19 pandemic in the philippines, rise the women leaders of the bangko sentral ng pilipinas, central bank of the philippines january 3, 1949 - january 3, 1974, 50 years of central banking in the philippines, the bangko sentral and the philippine economy.

History Wrought in Gold

Money and Banking in the Philippines

Perspectives from the Bangko Sentral ng Pilipinas

Perspectives on the Bangko Sentral ng Pilipinas Painting Collection

History and Heritage in Philippine Money The Numismatic Collection of the Bangko Sentral ng Pilipinas

Cool Minds, Brave Hearts

The People of the Philippine Central Bank

50 Years of Investing in Philippine Cultural Heritage

Enduring Legacies of Filipino Artistry

Central Banking in Challenging Times

The Philippine Experience

Philippine Central Banking

A Strategic Journey to Stability

The Governors Speak

Select speeches of the Governors of the Central Bank of the Philippines and Bangko Sentral ng Pilipinas

Volume I | Volume II | Volume III

F. MANUAL OF REGULATIONS

Manual of regulations for banks.

The Manual of Regulations for Banks (MORB) is the primary source of regulations governing entities supervised by the Bangko Sentral ng Pilipinas. It provides the rules and policy issuances that implement the broader provisions of Republic Act No. 8791, also known as the General Banking Law of 2000, as wella s other pertinent banking laws.

Manual of Regulations for Non-Bank Financial Institutions

The Manual of Regulations for Non-Banks Financial Institutions (MORNBFI) consolidates Philippine rules and policy issuances governing quasi-banks, investment houses, non-stock savings and loan associations and pawnshops in the country.

Manual of Regulations on Foreign Exchange Transactions

The Manual of Regulations on Foreign Exchange Transactions is a consolidation of all regulations governing foreign exchange transactions. This Manual replaces Circular No. 1389 dated 13 April 1993, as amended, which was the first consolidation of foreign exchange regulations. This is an enhanced and complete version of Circular No. 1389, as amended, as it incorporates all amendments made since 1993 and consolidates all regulations on foreign exchange and related transactions.

Manual of Regulations for Payment Systems

The Manual of Regulations for Payment Systems (MORPS) compiles payment system regulations approved by the Monetary Board of the Bangko Sentral.

G. DIRECTORIES

Directory of philippine exporters.

A ready reference and easy guide to foreign buyers of Philippine products, local suppliers of exporters, foreign investors, government agencies, commercial banks and the interested public in general.

H. RESEARCH BLOG

The BSP Research Blog presents the views and analysis of BSP researchers based on BSP publications, current research and developments.

I. RESEARCH HUDDLE

The Research Huddle Seminar Series features ongoing and completed research work by BSP researchers and invited guests. It is a weekly forum of free and open discussion held every Wednesday from 1:30 p.m. to 2:30 p.m.

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