A DSGE Model on Unemployment in the Philippines:
Assessing the Impact of Fiscal and Monetary Policies
Academic Year 2015, Summer Semester

Submitted by: Tatum Blaise Pua Tan
Advisers: Professor Hiroaki Miyamoto, Professor Kenichi Ueda,
and Professor Takeki Sunakawa
Graduate School of Public Policy
The University of Tokyo

ABSTRACTThis paper is an antecedent application of the DSGE framework that incorporates
labor search theory to the Philippines, in an effort to examine and analyze theimpact of expansionary fiscal and monetary shocks on output and unemployment.
Results of the calibrated baseline model show that both fiscal and monetaryshocks cause output expansion and an increase in vacancies, leading to a decline
in the unemployment rate. A fiscal shock leads to a rise in the hours worked and afall in investment, consumption, and wage rates, while a monetary shock results
in a rise in all listed variables. It is also noted that the fiscal shock exhibits more
persistent effects on the economy and labor market than a monetary one. The
simulations are also able to identify the potential areas for enhancement in thecalibrated model, in order to better capture the impact of shocks on output andunemployment in the future. Overall, the current model allows us to advance ourunderstanding of unemployment dynamics in the Philippines, and assess theeffectiveness of policies in stimulating growth and addressing unemployment in
the country.

Keywords: DSGE, Labor Search, Unemployment in the PhilippinesACKNOWLEDGEMENTSI
I would like to express my utmost gratitude to Professor Hiroaki Miyamoto, forgenerously imparting his knowledge and extending ceaseless support during themaking of this research paper, until its conclusion.
I further extend my most sincere thanks to my supervisor, Professor Kenichi Ueda,
for providing his expertise and views on the subject.
My gratitude also goes to Professor Takeki Sunakawa for his keen guidance andvaluable insights, which really helped improve my work during the process.
My heartfelt appreciation goes out to friends, colleagues, and classmates, whowere my proofreaders, data and technical support providers, and mycheerleaders!
I also want to say thank you to my family for their unwavering support andencouragement. Lastly, I am grateful to the Almighty for all the divine intervention
that has given me the will and strength to complete this coursework.

TABLE OF CONTENTS
1 Introduction ...................................................................................................................... 1
2 Review of Related Literature ...................................................................................... 4
3 The Model .......................................................................................................................... 7

3.1 The Labor Market ................................................................................................................. 7
3.2 Households ............................................................................................................................. 8
3.3 Intermediate Goods Firm ................................................................................................10
3.4 Retailers and Price Setting ..............................................................................................11
3.4 Wage and Hours Bargaining ...........................................................................................13
3.5 Monetary/Fiscal Policies and Closing the Model ....................................................13

4 Calibration ...................................................................................................................... 15
5 Impulse Response Functions and Analysis ......................................................... 17
5.1 Fiscal Shock ..........................................................................................................................17
5.2 Monetary Shock...................................................................................................................18

6 Conclusion ...................................................................................................................... 20
References .......................................................................................................................... 25
TablesTable 1: Policy Rate Reductions by the BSP during the Crisis ............................... 3
Table 2: Calibration of Parameters................................................................................... 15
FiguresFigure 1: Cross-country GDP Growth .................................................................................. 1
Figure 2: Cross-country Unemployment Rate ................................................................ 1
Figure 3: Impulse Responses to a Fiscal Shock.......................................................... 18
Figure 4: Impulse Responses to a Monetary Shock .................................................. 19
Figure 5: Cross-country Labor Force Expansion........................................................ 20
Figure 6: Real Minimum Wage, NCR ................................................................................. 20
Appendices
Appendix 1: Steady State Conditions ............................................................................... 22
Appendix 2: Log-linear Equilibrium Conditions ........................................................ 23

1 Introduction
The Philippines has displayed a remarkable economic performance in recent
years, exhibiting resilience amid a series of global economic downturns, as seen in
Figure 1. This is mainly on account of the country’s sound macroeconomic
fundamentals, supported by expansionary fiscal and monetary policies
undertaken by the authorities to keep the economy afloat during these crisis
periods. However, robust economic growth has not progressed as swiftly as
expected in terms of making a2: Cross-country GDP Growthdefinite impact on the labor FigureFigure
1: Cross-Country GDP Growthmarket. This has prompted some
economists to dub it, a “jobless 10
growth.” It may be noted that thePhilippines has registered the 8highestunemployment
rate 6
relative to its peers in the region,
hovering at seven to eight percent 4
for almost a decade, as shown in
Figure 2. Hence, the persistently 2high rate of unemployment
0
continues to be one of the core2005 2006 2007 2008 2009 2010 2011 2012 2013
issues confronting the nation, and a -2
significant challenge for policy
Indonesia
Korea, Republic of
Malaysia
1: Cross-country
Unemployment
makers. After redeeming itself FigurePhilippines
Thailand
Viet Namfrom being the region’s economic RateFigure 2: Cross-Country Unemployment Rate
laggard, the Philippines now faces 12
rising pressure to successfully 10translate“growth”
intoameasurably
lower
rate
of 8
unemployment.
6

Despitethecentralrole
unemployment plays in thePhilippine economy, its inclusion
remains limited in academic
papers employing contemporary
empirical models. Thus, themotivation of this research is
twofold. First, this researchintends to set the stage for the useof Dynamic Stochastic General
Equilibrium (DSGE) models that
integrate labor search theory to
study unemployment, which to myknowledge is the first of such
undertaking
based
on
the
Philippines. Labor search theory is

4
2
0
2005

2006
Indonesia
Philippines

2007

2008

2009

2010

Korea, Republic ofThailand

2011

2012

2013

Malaysia
Viet Nam

Note: In 2005, the National Statistical
Coordination Board (NSCB) implemented theinclusion of a third criterion that is the person
must also be available for work—in paid or selfemployment—during the basic survey reference
period. In addition, a six-month
cut-off period
for the job search of the discouraged workers was
imposed.
Source: www.adb.org

1

a popular model in evaluating structural unemployment due to the mismatch
between heterogeneous workers and jobs. According to Rocheteau (2006), thetheory of unemployment has three key components: wage setting, posting job
vacancies, and the matching of jobs and workers. In order to better analyze
unemployment, it is essential to assimilate these elements into the framework.
This research adopts a highly stylized model by combining papers by Kato andMiyamoto (2012) and Kuo and Miyamoto (forthcoming). However, the fairly
prefatory nature of this work warrants the adoption of a relatively simplified
calibrated model. I believe that this study can serve as a sound groundwork for
future development of more powerful models encompassing unemployment
dynamics.
To shed light on the dynamics involved in the theory of unemployment, Rocheteau(2006) provides the following explanation of the key elements. First, firms andtheir employees undergo a bargaining process to determine the wages, wherein
the party with more leverage gains the bigger fraction of the surplus. Second,
posting job vacancies and hiring new workers not only takes time, but also entails
costs like advertising and evaluating applicants. Therefore, firms will only hire
employees if the benefits outweigh the costs. Lastly, the matching function depicts
the relationship between the number of unemployed, the number of vacancies, andthe number of jobs created. As the pool of unemployed people expands, job seekers
will experience a congestion effect that adversely affects their probability offinding a job successfully. This shows that the matching mechanism is neithersmooth nor instantaneous.
The second motivation of this research is to broaden the analysis of the impact of
expansionary fiscal and monetary policies not only on growth, but also on
unemployment. Like many other countries during the recent global crisis, thePhilippine government launched its own stimulus package—the Emergency
Resiliency Plan (ERP) amounting to P330 billion pesos (4.1 percent of GDP)— inan effort to stimulate the economy (Doraisami, 2011). 1 Although the specificchannels where these funds were directed substantially influenced the stimulus’
effectiveness, this study takes a more macroeconomic approach by examining thebroader impact of fiscal expansion on the economy and the labor market. Whilesome DSGE papers in the Philippines have already examined the effect of fiscal
spending using New Keynesian models, the analysis on the labor market havebeen limited to labor demand and hours worked (see McNelis, Glindro, Co, andDakila, 2009 and Majuca, 2011). Therefore, to provide the link that will enable thecurrent analysis to extend to unemployment, this research incorporates theMortensen-Pissarides (1994, as in Kato and Miyamoto, 2012) search andmatching model into the existing framework.
Furthermore, I have extended my assessment to include the impact of a negative
monetary shock on the economy and unemployment. It may be noted that unlike
1 Doraisami (2001) details the ERP package as follows: P160 billion of national spending on

community-level infrastructure projects and social protection measures; P100 billion to financeextra-budgetary infrastructure projects and large infrastructure projects; P30 billion for new andtemporary additional benefits to SSS, GSIS and PhilHealth; and P40 billion in income tax cuts.

2the US Federal Reserve
Table 1: Policy Rate Reductions by the BSP
Bank which has theduring the Crisis
statutory objectives to not
only ensure stable prices
but also facilitate maximum
employment, the Bangko
Sentral ng Pilipinas’ (BSP)
sole objective in conducting
monetary policy under an
inflation-targeting
framework is price stability.
Source: Guinigundo, Diwa C. (2009). The Impact of the
It should be noted however,Global Financial Crisis on the Philippine Financial Systemthat during the recent– An Assessment. Bank for International Settlements (BIS)
global downturn the BSP
Papers No. 54, 332.
implemented a series ofpolicy rate reductions to aid the weakening economy, as shown in Table 1. Thisbrought the overnight reverse repurchase rate (RRP) and the repurchase rate(RP) down to 4.0 and 6.0 percent, respectively (Guinigundo, 2009). While themove was directly intended to stave off economic slowdown by stimulating
business and household activities, such an expansion could have a spillover effectinto the labor market. Employing the same calibrated DSGE model, this study
examines the effect of a one standard deviation monetary shock to the economy
and the unemployment rate.
The results of the study show that a shock on fiscal spending leads to a decline of
the unemployment rate attributable to the expansion of output and increase invacancies posted by firms. A fiscal shock also leads to a rise in hours worked but
at the same time, results in a fall in investment, consumption, and wage rates.
Similarly, an expansionary monetary policy shock lowers the unemployment rate.
However, the impact of the shock on some variables, particularly the rise in
output, investment, hours worked, and vacancies, appear to be transitory. In
addition, the simulations in the calibrated baseline model enable the identificationof key areas for improvement in the framework to better capture the effect ofmonetary and fiscal shocks on the economy. Overall, a fiscal shock exhibits more
persistent effects on the economy and the labor market than a monetary shock.
The rest of the paper is organized as follows: Section II provides a review of therelated literature; Section III presents the estimated DSGE model, providing
details of the functions used for the labor market, households, firms, andauthorities; Section IV covers the calibration; Section V presents and analyzes theimpulse response functions; and Section VI concludes.

32 Review of Related Literature
There are already a number of research papers employing DSGE in the Philippines,
including the work by McNelis, et al. (2009), which develops a small open
economy DSGE model for the Philippines to assess the impact of fiscal andmonetary policies in the economy. Their results indicate that a 25bps reduction in
the RRP rate leads to higher prices and inflation as well as an initial exchange rate
depreciation, translating to a modest output growth. This is fuelled by theincreased production in the tradable sector, which raises labor demand. However,
the rise in price level prevails over the depreciation, causing a real exchange rate
appreciation, which in turn causes a bigger output contraction later on.
Meanwhile, a fiscal stimulus amounting to one percent of GDP initially raises
output, mainly propelled by the non-tradable sector, translating to higher labordemand. Likewise, nominal wages and prices increase, feeding into inflation,
which in turn provides an impetus to raise interest rates. This eventually leads toa real exchange rate appreciation and a deterioration of the current accountbalance, thereby lowering output and inflation. Overall, the research finds that theeffect of monetary policy is more pronounced on the tradable sector, while theeffect of fiscal policy is more prominent on the non-tradable sector. Although theirresearch covers the impact of both policy actions, it does not delve into thespecifics of the labor market reasonably. Hence, my study will focus on thisuntapped area.
Similarly, Majuca (2011) develops a medium-scale closed economy DSGE modelfor the Philippines using a multi-period sample (pre- and post-IT) to evaluatecredibility gains from inflation targeting, which the BSP adopted in 2002. The
paper includes a significantly more comprehensive set of frictions, namely:
investment adjustment costs, habit formation, price and wage rigidities, variable
indexation, fixed costs, as well as price and wage indexation. Empirical results ofthe model find that an increase in the BSP’s policy decreases output, consumption,
investment, wages, and inflation, while increasing the interest rate. The study also
simulates an exogenous spending shock, corresponding to a demand shock, which
covers shocks to both government spending and net exports. An increase in thisexogenous spending raises output, hours worked, wages, and inflation, but causes
consumption, investment, and BSP policy rates to fall. In addition, the researchconcludes that the Philippine economy is more stable with lower risk aversion in
the post-IT era.
Among the relatively early works that incorporate elements of labor market
matching functions in DSGE models is that of Walsh (2003), which examines therole of labor market matching function and price stickiness in influencing theimpact of monetary shocks, in the form of money growth, to the economy. The
representative household in his model consists of workers and shoppers facing autility maximization problem with two constraints—the resource constraint anda cash-in-advance constraint (i.e. income in period t cannot be used for
consumption until t+1). This allows the nominal interest rate to influence thediscounted value current production, and subsequently output and employment
as well. The labor search dynamics and price stickiness are integrated through theinclusion of a wholesale sector, where matched firms and workers generate4output, and a monopolistically competitive retail sector facing sticky prices. The
study finds that under sticky prices, the expansionary monetary shock increases
output, employment, and job creation while at the same time, decreases job
destruction reducing the number of job seekers.
In tackling a relatively similar issue to the above research, Galí (2010) simulates
the impact of a contractionary monetary policy shock to the US economy, using a
Taylor-type interest rate rule with an exogenous policy shifter. The paper extends
the New Keynesian model to distinctly incorporate labor market frictions andunemployment, as well as highlights the effect of the presence of price and wage
stickiness on the impact of the shocks. The model offers two alternative wage
settings—employing Nash bargaining to represent the case of flexible wages andincorporating staggered nominal wage setting à la Calvo (1983) for sticky wages.
Results in Galí’s calibrated model show that a monetary policy shock with priceand wage stickiness leads to a fall in output, inflation, and employment as well as
an increase in unemployment. Although, the decline in inflation is more muted in
the case of sticky wages. Galí also finds that the effect of labor market frictions to
the response of the economy’s equilibrium dynamics, in the context of an economy
with rigidities and Taylor-rule monetary policy to shocks, is quite limited. Lastly,
the study covers comparisons on the optimal monetary policy design withsimulated technology shocks. However, this is outside the scope of my research.
Faccini, Millard, and Zanetti (2011) likewise employ a model that integrates
matching frictions as well as á la calvo price and wage rigidities to the New
Keynesian framework using UK data. They reckon that the introduction of thesefrictions enhanced the robustness of their model, facilitating a better fit with thedata. Sans wage stickiness, they find that a one standard deviation monetary
policy shock results in a decline in output, consumption, investment, priceinflation, employment, hours worked, unit labor costs, and vacancies. While thetrend of the variables appears to be generally the same in the case of sticky wages,
except for wage inflation and unit labor costs, the magnitude varies. The model
also offers an estimate on vital structural variables, which helps shed light on thetransmission mechanism of shocks in light of wage rigidities, and the key
economic factors driving the economic fluctuations in the country. However, theirstudy shows that wage rigidities are extraneous in the inflation dynamics due tothe offsetting effect of unit labor costs and search costs. It may also be noted that
unlike my study which employs a Nash wage bargaining system, their study
employs a sharing rule wherein the fraction of the total surplus owing to theworkers corresponds to their bargaining power, following Thomas (2008, as inFaccini, et al., 2011).
Mixed conclusions can be drawn from the different literature on the impact offiscal shocks on unemployment. On one hand, Kato and Miyamoto (2012) find that
fiscal expansion improves labor market condition in Japan. Their research isrelated to that of Monacelli, Perotti and Trigari (2010, as cited in Kato Miyamoto,2012), which studies the impact of fiscal policy in the US, but differs as it allows
adjustment in in the intensive margin of labor. Kato and Miyamoto (2012) use
both a structural VAR (SVAR) model and a dynamic general equilibrium modelwith search and matching frictions akin to Mortensen and Pissarides (1994, as
5

cited in Kato and Miyamoto, 2012). Using the SVAR model, they find that fiscal
expansion decreases unemployment and increases employment, andcorrespondingly improves the job finding rate while easing the job separation
rate. Although the DSGE model finds similar patterns on the effect of government
spending on labor market variables (i.e. increases in output, hours worked per
worker and vacancies, as well as decline in unemployment rate), the magnitude of
the impact differs. While this is one of the materials that this paper draws from,my research employs an expanded resource constraint faced by the household toinclude government bond holdings, at the same time extends the analysis toinclude the monetary sector.
On the other hand, Mayer, Moyen, and Stähler (2010) find that a fiscal shock could
increase unemployment, contingent upon the persistence of the fiscal shock andthe kind of household. They reckon that a transitory fiscal expansion is likely to beineffective if the firms’ hiring decisions are more forward looking. In other words,
firms could benefit from creating jobs as the marginal profit of a worker rises
during the period, but the new matches are unlikely to survive. Moreover, theirmodel differs from the previously cited research as it differentiates between
optimizing households that save and liquidity constrained households that consume
all their labor income, whose consumption behavior run in opposite directions
following an augmented fiscal spending. They infer that incentive for the latter to
put in more hours diminishes because the marginal utility of consumption
declines relative to the marginal disutility of hours working. Therefore if liquidity
constrained households dominate the market, fiscal expansion results in an
increase in unemployment notwithstanding the persistence of the shock.

6

3 The Model
This research offers a precursor application of a DSGE framework incorporating
labor search theory in the New Keynesian model to the Philippines, in order toexamine and analyze the impact of fiscal and monetary shocks on output andunemployment. The inclusion of labor search theory enables the model to better
capture unemployment dynamics by accounting for the fact that hiring and job
seeking both entail costs and time, rather than the idea of workers seamlessly
flowing in and out of the market (Mortensen and Pissarides, 1994 and Pissarides,
2000, as cited in Walsh, 2003). The methodology fundamentally combines themodels by Kato and Miyamoto (2012) and Kuo and Miyamoto (forthcoming) todevelop a more straightforward model. The economy in this study consists of thehouseholds, competitive intermediate firms, monopolistically competitive
retailers, and both monetary and fiscal authorities. Using this mix of market agents
allows policy analysis to extend to cover the impact of monetary and fiscal policies
on output and unemployment.

3.1 The Labor Market
As mentioned earlier, firms and workers undergo a laborious search processcompelled by the frictions inherent in the market, which otherwise would allow
perfect movements in the labor flow. This paper integrates this condition in thegeneral model by utilizing the following standard matching function of the CobbDouglas form
𝜉 1−𝜉𝑚𝑡 = 𝑀𝑡 𝑢𝑡 𝑣𝑡.

where 𝑚𝑡 is the number of matches, 𝑢𝑡 is the number of job-seekers, 𝑣𝑡 is thenumber of vacancies posted by the intermediate firms, and 0 < 𝜉 < 1 denotes theelasticity of the matching function with respect to unemployment. Moreover, thetime-varying matching efficiency, 𝑀𝑡 , follows the stochastic process2 ).
log 𝑀𝑡 = (1 − 𝜌𝑀 ) log 𝑀 + 𝜌𝑀 log 𝑀𝑡−1 + 𝜀𝑀,𝑡 , 𝜀𝑀,𝑡 ~𝑁(0, 𝜎𝑀

During each period, the probability that a vacancy is filled is represented by 𝑞𝑡 =𝑚𝑡
⁄𝑣𝑡 = 𝑀𝑡 𝜃𝑡 −𝜉 , while the probability that a job seeker is employed is𝑚represented by 𝑝𝑡 = 𝑡⁄𝑢𝑡 = 𝑀𝑡 𝜃𝑡 1−𝜉 . The labor market tightness is then𝑣
denoted by 𝜃𝑡 = 𝑡⁄𝑢𝑡 .
At the beginning of a period t, intermediate firms search for new hires by postingvacancies 𝑣𝑡 , at the same time, 𝑢𝑡 unemployed workers look for jobs. This process
results in new matches 𝑚𝑡 . New hires are assumed to start working and become
productive immediately within the same period. Consequently, a constant fractionof workers loses their job at the end of each period and will not be able to search
for a new one until the following period t +1. Thus, the evolution of employment
is as follows
𝑛𝑡 = (1 − 𝑠)𝑛𝑡−1 + 𝑚𝑡 = (1 − 𝑠)𝑛𝑡−1 + 𝑝𝑡 𝑢𝑡 = (1 − 𝑠)𝑛𝑡−1 + 𝑞𝑡 𝑣𝑡 .

(1)
7

Meanwhile, the number of job seekers is represented by
𝑢𝑡 = 1 − 𝑛𝑡−1 + 𝑠𝑛𝑡−1 .
Hence, at time t, the number of employed workers is the sum of last period’s
workers who were able to retain their jobs and the new hires/newly filledvacancies, while the corresponding number of unemployed workers is given by
𝑈𝑡 = 1 − 𝑛𝑡 .

3.2 Households
As in Kuo and Miyamoto (forthcoming), the representative household consists ofa continuum of infinitely lived workers of measure one. A household member iseither employed or unemployed. Employed members provide labor and earn
wages, while the unemployed look for jobs. Every household consumes final
goods, accumulates capital, acquires government bonds, and acts as shareholdersof the intermediate goods firms. It is likewise assumed that the households
decides on a utilitarian basis and thus, consumption is identical for each member
regardless of employment status. Following Merz (1995, as in Kuo and Miyamoto,forthcoming), members of the representative household are provided perfectconsumption insurance by one another against unemployment risks or income
variability.
The representative household’s lifetime utility function is akin to Kato andMiyamoto (2012) and incorporates 𝛾𝑡 and 𝜒𝑡 , which denotes the preference andlabor supply shocks, respectively. It is characterized by
𝐶 1−𝜎

𝑡
𝑡
𝔼 0 ∑∞
𝑡=0 𝛽 [𝛾𝑡ℎ1+𝜇− 𝜒𝑡 Φ𝑛𝑡 𝑡 ] ,
1−𝜎
1+𝜇

(2)

where 𝛽 is the household’s subjective discount factor, 𝐶𝑡 is private consumption,ℎ𝑡 is the individual hours of work, Φ > 0 measures the disutility of labor supply,
𝜎 governs the degree of risk aversion or the inverse of the intertemporal elasticity
of substitution, and 𝜇 is the inverse of Frisch elasticity of labor supply. The habit
persistence perimeter is excluded selectively from the equation for simplicity.2
Note that the added preference shock 𝛾𝑡 and labor supply shock 𝜒𝑡 follow a firstorder autoregressive process with i.i.d.-normal error termlog 𝛾𝑡 = 𝜌𝛾 log 𝛾𝑡−1 + 𝜀𝛾,𝑡 ,

𝜀𝛾,𝑡 ~𝑁(0, 𝜎𝛾2 ),log 𝜒𝑡 = 𝜌𝜒 log 𝜒𝑡−1 + 𝜀𝜒,𝑡 ,𝜀𝜒,𝑡 ~𝑁(0, 𝜎𝛾2 ).

2 McNelis, et al. (2009) assigns a lower value of habit persistence in their DSGE model for thePhilippines vis-à-vis in the values used US studies, citing the Filipino consumers’ less habitualcharacteristic due to a higher degree of income uncertainty.

8Moreover, given the capital stock 𝐾𝑡 in period t and depreciation rate 𝛿 , thehousehold accumulates capital and achieves the desired level of capital 𝐾𝑡+1 in thefollowing period by investing 𝐼𝑡 . Employing evolution of capital by Faccini, et al.
(2011), capital accumulation takes the form
𝐾𝑡+1 = (1 − 𝛿)𝐾𝑡 + Ψ𝑡 𝐼𝑡 ,(3)

where Ψ𝑡 is an investment shock, which follows a stochastic processlog Ψ𝑡 = 𝜌Ψ log Ψ𝑡−1 + 𝜀Ψ,𝑡 ,𝜀Ψ,𝑡 ~𝑁(0, 𝜎𝛾2 ).

The representative household’s budget constraint is characterized by𝑅𝑏𝑡
𝐶𝑡 + 𝐼𝑡 + 𝑏𝑡+1 = 𝑛𝑡 𝑤𝑡 ℎ𝑡 + (1 − 𝑛𝑡 )𝑧 + 𝑟𝑡𝐾 𝐾𝑡 + 𝑡−1+ 𝐷𝑡 − 𝜏𝑡 ,
𝜋

(4)

𝑡

where 𝑏𝑡 is acquisition of government bond, 𝑛𝑡 𝑤𝑡 ℎ𝑡 is the total labor income
earned by all employed workers, z is the unemployment benefits, 𝑟𝑡𝐾 is the rental
rate of capital, 𝑅𝑡 is the nominal interest rate, 𝜋𝑡 is the price ratio, 𝐷𝑡 is thedividend receive by the households from the firms, and 𝜏𝑡 represents the
lump-sum taxes paid to the government. Note that unemployment benefits do notnecessarily refer to unemployment insurance from the government, rather it
accounts for the outside opportunities available to the member who is notworking (e.g. engaging in home production).
The household maximizes its lifetime utility (2) subject to the employment
constraint (1), capital accumulation equation (3), and the budget constraint (4),by choosing the optimal levels of 𝐶𝑡 , 𝐼𝑡 , 𝐾𝑡+1 , 𝑏𝑡+1 , and 𝑛𝑡 . This yields the following
first-order conditions:
𝜆𝑡 = 𝛾𝑡 𝐶𝑡−𝜎 ;𝜆𝑡 = 𝜆𝐾𝑡 Ψ𝑡 ;𝐾
𝐾
𝜆𝐾
𝑡 = 𝛽 [𝜆𝑡+1 𝑟𝑡+1 + 𝜆𝑡+1 (1 − 𝛿)] ; and𝜆𝑡 = 𝛽 (𝜆𝑡+1

𝑅𝑡+1
),
𝜋𝑡+1

where 𝜆𝑡 and 𝜆𝐾
𝑡 are the Lagrange multipliers associated with the budget

constraint and the capital accumulation equation, respectively.

To derive the marginal value of an employed worker to the household 𝒲𝑡 , the9first-order derivative with respect to employment is taken
𝜒 ℎ

1+𝜇

𝒲𝑡 = 𝑤𝑡 ℎ𝑡 − 𝑧 − Φ 𝑡 𝑡

𝜆𝑡 1+𝜇where 𝒲𝑡 =

𝜆𝑛
𝑡
𝜆𝑡

𝜆

+ 𝛽 𝔼𝑡 [(1 − 𝑠)(1 − 𝑝𝑡+1 ) 𝑡+1 𝒲𝑡+1 ] ,𝜆𝑡(5)and 𝜆𝑛𝑡 is the Lagrange multiplier associated with the constraint

pertaining to the evolution of employment. The equation implies that the marginalvalue of a job to an employed worker is equal to the wage net of unemployment
benefits and the disutility of work plus the expected discounted value of being
employed next period.

3.3 Intermediate Goods Firm
The representative intermediate goods firm hires labor and rents capital from thehouseholds and produces homogeneous intermediate goods, which are then soldto the final goods firms in a competitive market. As in Kuo and Miyamoto(forthcoming), the intermediate goods firm produce output according to thefollowing production function, which assumes a constant returns to scale
production, whereby capital-labor ratio across all firms is the same,𝑦𝑡 = 𝐴𝑡 𝑘𝑡𝛼 (𝑛𝑡 ℎ𝑡 )1−𝛼(6)where 0 < 𝛼 < 1 is the capital share and 𝐴𝑡 is an exogenous stochastic variable
that captures neutral technology shocks
log 𝐴𝑡 = 𝜌A log 𝐴𝑡−1 + 𝜀A,𝑡 ,𝜀A,𝑡 ~𝑁(0, 𝜎𝛾2 ).

The intermediate good firm maximizes the present value of its lifetime profit bychoosing the optimal number of employees 𝑛𝑡 , number of vacancies 𝑣𝑡 , and levelof capital 𝑘𝑡∞

𝔼0 ∑ [𝛽 𝑡𝑡=0𝜆𝑡(𝑥 𝑦 − 𝑤𝑡 𝑛𝑡 ℎ𝑡 − 𝑟𝑡𝐾 𝑘𝑡 − 𝜅𝑣𝑡 ) ]𝜆0 𝑡 𝑡subject to the employment constraint (1) and production function (6). Since thehouseholds hold the equities of intermediate goods firms, said profits are
estimated using the household’s discount factor in terms of marginal utility 𝜆𝑡 . The
competitive price of intermediate goods is given by 𝑥𝑡 , while the wage 𝑤𝑡 is set
through a bargaining process. The cost of posting a vacancy is denoted by 𝜅.

The representative intermediate firm’s optimal decision with respect to capital̃and employment, with a Lagrange multiplier 𝜆𝑛𝑡 assigned to the latter, results inthe following first-order conditions
10

𝑟𝑡𝐾 = 𝛼𝒥𝑡 = (1 − 𝛼)where 𝒥𝑡 =

̃
𝜆𝑛
𝑡

𝜆𝑡

𝑥𝑡 𝑦𝑡
𝑛𝑡

𝑥𝑡 𝑦𝑡
𝑘𝑡

and
𝜆

− 𝑤𝑡 ℎ𝑡 + 𝛽(1 − 𝑠) 𝔼𝑡 ( 𝑡+1 𝒥𝑡+1 )

(7)

𝜆𝑡

represents the marginal value of a worker to the firm. The

equation indicates that the marginal value of a worker to a firm corresponds tothe marginal revenue product of employment net of wages paid and the expecteddiscounted value of retaining the worker the next period.
Furthermore, evaluating the first-order condition with respect to vacancy yields

𝜅=

̃
𝜆𝑛
𝑡

𝜆𝑡

𝑞𝑡 = 𝒥𝑡 𝑞𝑡 ,(8)

which leads to the job creation condition—combing (7) and (8),𝜅𝑞𝑡

= (1 − 𝛼)

𝑥𝑡 𝑦𝑡
𝑛𝑡

𝜆

− 𝑤𝑡 ℎ𝑡 + 𝛽(1 − 𝑠) 𝔼𝑡 ( 𝑡+1
𝜆𝑡

𝜅
𝑞𝑡+1

).

The above implies that the marginal cost of hiring a worker is equal to themarginal benefit generated by hiring an additional worker to the firm, which is themarginal revenue product of employment net of wages paid and the deterred costs
associated with having to post a vacancy in the next period.

3.4 Retailers and Price Setting
The homogenous intermediate goods are then sold to a continuum ofmonopolistically competitive retailers, indexed by 𝑗𝑡 , which transform them into
differentiated retail goods on a one-for-one ratio.
Following Kuo and Miyamoto (forthcoming), a retailer 𝑗𝑡 sells Υ𝑗,𝑡 quantity of goods
under the retail price 𝑃𝑗,𝑡 . The Dixit-Stiglitz aggregator of the bundle of individual
retail goods is characterized by𝜖𝑡
1 𝜖 −1𝜖−1𝑡𝑡𝜖𝑡Υ𝑡 = (∫ Υ𝑗,𝑡
𝑑𝑗)
0

where 𝜖𝑡 is the elasticity of substitution across the differentiated retail goods,
which governs the price mark-up, and is assumed to follow a stochastic process
log 𝜖𝑡 = (1 − 𝜌𝑀 ) log 𝜖 + 𝜌𝑀 log 𝜖𝑡−1 + 𝜀𝜖,𝑡 ,2 ).
𝜀𝜖,𝑡 ~𝑁(0, 𝜎𝑀

11Each retailer 𝑗𝑡 faces the following demand for its product𝑃𝑗,𝑡 𝜖𝑡Υ𝑗,𝑡 = (

𝑃𝑡

)

Υ𝑡 ,

where the cost minimizing aggregate price index 𝑃𝑡 is
1

1 1−𝜖
1−𝜖
𝑃𝑡 = (∫0 𝑃𝑗,𝑡 𝑡 𝑑𝑗) 𝑡 .

Á la Calvo (1983), it is assumed that only a fraction (1 − 𝜑)of retailers are able tore-optimize their prices each period. On one hand, for the jth retailer who is unable
to re-optimize, its product price 𝑃𝑗,𝑡 conforms to the following partial indexation
scheme𝜄𝑝
𝑃𝑗,𝑡 = 𝜋𝑡−1
𝜋 1−𝜄𝑝 𝑃𝑗,𝑡−1,

where 𝜄𝑝 represents the backward-looking parameter governing inflation,𝜋𝑡−1 =

𝑃𝑡

𝑃𝑡−1

indicates the gross inflation rate in period 𝑡 − 1, and 𝜋 denotes thesteady-state inflation.
On the other hand, the retailer who is able to re-optimize at time t chooses the
optimal price 𝑃̃𝑡 by evaluating the following profit maximization function subject
to the subsequent aggregate demand function faced by each retailer 𝑗𝑡 undermonopolistic competition∞

max 𝔼𝑡 {∑ (𝛽𝜑)𝑘
𝑃̃𝑡

𝑘=0

𝜆𝑡+𝑘 (𝑃̃𝑡 ℱ𝑡,𝑘 − 𝑃𝑡+𝑘 𝑥𝑡+𝑘 )̃𝑡+𝑘 ]}
Υ
[
𝜆𝑡
𝑃𝑡+𝑘
̃

−𝜖𝑡

̃𝑡+𝑘 = ( 𝑃𝑡ℱ𝑡,𝑘)Υ
𝑃𝑡+𝑘

Υ𝑡+𝑘 .

The compound effect of partial indexation is described by ℱ𝑡,𝑘 , wherein
𝜄

𝑝
𝑘
1−𝜄𝑝
ℱ𝑡,𝑘 = {∏𝑘=1 𝜋𝑡+𝑘−1 𝜋1

𝑘 ≥ 1.
𝑘=0

The resulting first-order condition with respect to 𝑃̃𝑡∞̃𝑡+𝑘 (𝑝̃𝑡 ℱ𝑡,𝑘 −𝔼𝑡 [∑ (𝛽𝜑)𝑘 𝜆𝑡+𝑘 (1 − 𝜖𝑡+𝑘 ) Υ
𝑘=0

𝜖𝑡+𝑘
∏ 𝑥 )] = 0
𝜖𝑡+𝑘 − 1 𝑡,𝑘 𝑡+𝑘12

where

𝑝̃𝑡 =

𝑃̃𝑡
𝑃𝑡

𝜄

and

𝑝
𝑘
∏𝑡,𝑘 = {∏𝑘=1 𝜋𝑡+𝑘1

𝑘 ≥ 1 . The equation
𝑘=0

indicates that accounting for partial inflation indexation and the possibility of
being stuck with this price in the succeeding periods, the optimal price selected byforward-looking re-negotiating firms should equal to the time-varying mark-up
𝜖𝑡+𝑘(Christiano, Trabandt, and Walentin, 2010 and Faccini, et al., 2011).
𝜖𝑡+𝑘 −1

3.4 Wage and Hours Bargaining
Due to the presence of labor market frictions, the wage rate 𝑤𝑡 and hours of work
per employee ℎ𝑡 are negotiated in a bilateral bargaining process between theworkers and the intermediate firm so as to divide the surplus accordingly given
the existing employment relations. Both variables are determined through Nashbargaining which aims to maximize the weighted average of the worker’s and thefirm’s surplus
𝜂 1−𝜂

max 𝒲𝑡 𝒥𝑡
𝑤𝑡 ℎ𝑡

where 𝜂 ∈ (0,1) governs the worker’s bargaining power.
Evaluating the first order conditions with respect to both wage and hours resultin the following wage and hours supply equations
𝑥𝑡 𝑦𝑡
𝜆𝑡+1
+ 𝛽 (1 − 𝑠)𝔼𝑡 (𝜅𝜃𝑡+1 )]𝑛𝑡
𝜆𝑡
1+𝜇
Φ 𝑥𝑡 ℎ𝑡+ (1 − 𝜂) (𝑧 +)1 + 𝜇 𝜆𝑡

𝑤𝑡 ℎ𝑡 = 𝜂 [(1 − 𝛼)(1 − 𝛼)2

𝑥𝑡 𝑦𝑡
𝑛𝑡 ℎ 𝑡ℎ𝜇= Φ 𝑡 𝜒𝑡 .
𝜆𝑡

Kuo and Miyamoto (forthcoming) explains that the wage equation connotes thatthe wage rate is equal to the weighted sum of the firm’s gains, in terms of marginal
revenue product and the continuation value of the worker, and the worker’s
opportunity cost, consist of the unemployment benefits and the disutility of labor.
Furthermore, the hours supply equation implies that the hours of work isestablished through the equalization of the marginal product of hours and themarginal rate of substitution between leisure and consumption.

3.5 Monetary/Fiscal Policies and Closing the Model
The Central Bank employs a Taylor rule framework where the nominal interest
rate is a function of the past interest rate 𝑅𝑡−1 and deviations of inflation 𝜋𝑡 and13

output Υ𝑡 from their respective steady state values—sans the subscript t. It isrepresented by
𝑅𝑡𝑅

𝑅𝑡−1 𝜌𝑅

= (

𝑅

)

𝜋𝑡 𝜙𝜋

[( 𝜋 )

1−𝜌𝑅
Υ𝑡 𝜙Υ

(Υ)

]

𝜁𝑚𝑝,𝑡 −1 ,where the parameter 𝜌𝑅 denotes the interest rate smoothing while 𝜙𝜋 and 𝜙Υgovern the response of the Central Bank to deviations of inflation and output fromtheir steady-state values. Moreover, monetary policy shocks 𝜁𝑚𝑝,𝑡 are i.i.d and israised to negative one to generate an expansionary shock.
Meanwhile, the spending aspect in the fiscal equation consists government
consumption 𝐺𝑡 , bond interest payments, and unemployment benefits, while thefinancing side includes lump-sum taxes and bond issuances.

𝜏𝑡 + 𝑏𝑡+1 = 𝐺𝑡 +𝑅𝑡𝑏 + (1 − 𝑛𝑡 )𝑧.
𝜋𝑡 𝑡Note that 𝐺𝑡 follows a stochastic process characterized aslog 𝐺̂𝑡 = 𝜌𝐺 log 𝐺̂𝑡−1 + 𝜀𝐺,𝑡 , 𝜀𝐺,𝑡 ~𝑁(0, 𝜎𝐺2 ),where 𝐺̂𝑡 ≡(𝐺𝑡 − 𝐺)
Υis the percentage deviation of government spending fromthe steady state output level and 𝜌𝐺 is the persistency of government
consumption.
Moving ahead, in the market clearing condition, the demand for capital goods by
the intermediate firms must equal the capital supplied by the households, i.e., 𝑘𝑡 =𝐾𝑡.
To close the model, the resource constraint of the economy is given byΥ𝑡 = 𝐶𝑡 + 𝐼𝑡 + 𝐺𝑡 + 𝜅𝑣𝑡 .

14

4 Calibration
Calibration is a commonly used method in DSGE literature in estimating
parameters. It provides a good indication of the model’s capability and allows theassessment of the implications of different policy scenarios (Mutschler, 2014).
This section explains the calibration of parameters for the baseline model in orderto match certain elements of the Philippine economy, presented in Table 2.
Following Kuo and Miyamoto (forthcoming), the elasticity of matching function 𝜉
is set at 0.6, a little higher than the conventional 0.5 in some literature. The
exogenous separation rate s approximated at 7.87 percent is derived using the
average of the data on separation rate for the Metro Manila/National Capital
Region from the Labor Turnover Statistics of the Bureau of Labor and
Employment Statistics covering the period 2003:Q1-2014:Q4. Similarly, thesteady state unemployment rate u at 7.32 percent is a simple average of theunemployment rate from 2005:Q1-2014:Q4 from the Labor Force Survey
published by the National Statistics Office (NSO).
Table 2: Calibration of Parameters

Parameter

Notation

Elasticity of matching function
Exogenous separation rate
Steady state unemployment rate
Discount factor
Degree of risk aversion
Inverse of Frisch elasticity
Unemployment benefits
Depreciation rate
Capital input elasticity of output in the
Cobb-Douglas production function
Cost of posting a vacancy
Calvo Parameter
Steady state gross inflation rate
Backward-looking parameter
governing inflation
Elasticity of demand to market share
Bargaining power
Steady state hours
Steady state government spending to
output ratio
Taylor Rule Parameters
Autoregressive parameter

𝜉
s
u
𝛽
𝜎
𝜇
z
𝛿
𝛼

0.6
0.07870.0732
0.99
2
0.25
0.15
0.05
0.36

𝜅
𝜑
𝜋
𝜄𝑝

0.05
2/3
1
0.5

𝜖
𝜂
h
g/y

11
0.6
1/3
0.116

Standard deviations

𝜌𝑅 , 𝜙𝜋 and 𝜙Υ𝜌𝐺𝜎𝐺 , 𝜎𝜁̂Value

0.9, 1.5, 0.1
0.8
0.1

15

The discount factor 𝛽 is set at 0.99, as in most literature, implying an annual realinterest rate of 4.0 percent. The degree of risk aversion is fixed at two, following
the DSGE literature on emerging market economies (EMEs) (see Boz, Durdu, andLi, 2012 and Epstein and Shapiro, 2014). Similarly, McNelis, et al. (2009) reckon
that the parameter is usually greater than 1.5 for EMEs. Consistent with McNelis,
et al. (2009), labor supply elasticity is placed at 0.25, implying a Frisch elasticity
of four. Since, there is no available data/literature to evaluate the value of
unemployment benefits and considering the absence of unemployment insurance
from the government in the Philippines, the study sets the parameter z at 0.15,
which is lower than that of Kato and Miyamoto (2012) at 0.20. The depreciation
rate 𝛿 is set at 0.05 percent, since developing countries are supposed to havehigher depreciation rate because of the relatively modest maintenance capability(Bu, 2006 as cited in Majuca, 2011). With reference to Majuca’s (2011) paper, theselected depreciation rate lies between the Majuca’s calculated implied
depreciation using firm-level data at 0.0575 percent per quarter and the estimate
used in his research at 0.04 percent per quarter.
Following Boz, et al. (2012), whose study examines the role of labor market
frictions in the business cycles experienced by EMEs, the capital input elasticity ofoutput in the Cobb-Douglas production function 𝛼 is estimated at 0.36. As in Kuo
and Miyamoto (forthcoming), the cost of posting a vacancy, the Calvo parameter,
and the elasticity of demand to market share are set at 0.05, 2/3, and 11,
respectively. The latter translates to a steady state profit margin of 10 percent for
the retailers. The steady state gross inflation rate is set at one, implying a zeroinflation rate. Consistent with Majuca (2011) the backward-looking parameter
governing inflation 𝜄𝑝 is estimated at 0.5.
Employing Kuo and Miyamoto’s (forthcoming) estimates for the worker’s
bargaining power and steady state hours of work per worker, 𝜂 and h are set at
0.6 and 1/3, respectively. The wage bargaining arrangement between the relevant
countries could share a common feature in a sense the workers’ bargaining power
is relatively constrained. Brooks (2002) explains that the minimum wage in thePhilippines is set by the Regional Tripartite Wages and Productivity Boards andrepresentatives from the government, businesses, and labor unions and thenreviewed by the National Wages and Productivity Commission to ascertain thatthe criteria for setting the minimum wage are met. The said study asserts thatwhile the government advocates an enterprise level collective bargaining for wage
setting, the coverage remains limited. In addition, the research mentions that
union representatives deem that some employers do not regard them as
collaborators in the pursuit of improving labor productivity and working
conditions.
Meanwhile, the Taylor Rule parameters 𝜌𝑅 , 𝜙𝜋 and 𝜙Υ follow that of Kuo andMiyamoto (2009) at 0.9, 1.5, 0.1, respectively. These values are also close to
Majuca’s (2011) conjecture of the Central Bank’s monetary reaction function
during post inflation targeting period and his prior on the interest rate feedback
from changes in the output gap. Lastly, the first order autoregressive parameterof the exogenous disturbances on government spending is set equal to 0.8 while
the standard deviations for both shocks are set equal to 0.1.
16

5 Impulse Response Functions and Analysis
5.1 Fiscal ShockThis section analyzes the impulse responses of selected variables to asingleperiod one standard deviation expansionary fiscal policy shock, especiallyunemployment, as shown in Figure 3. In the calibrated model, the fiscal shock
results in higher output and expansion in the intensive margin. The maximal effecton output and hours worked are observed immediately on impact and eases in thefollowing periods until they return to their steady state. This increase in spending
is of course financed by higher taxes. The combined effect of higher taxes andlower wages generate a negative wealth effect, while the higher interest rate
prompts a substitution effect. These factors compel the household to reduce
consumption and increase labor supply. Similarly, the augmented fiscal spending
pushes the interest rate up crowding out investments, which hits its trough in thesecond quarter.
The augmented government expenditure also causes a decline in the wages—theweighted sum of the firm’s marginal value of production (i.e. marginal product of
employment and expected costs saved associated with not having to post avacancy the next period) as well as the worker’s outside opportunities (i.e.
unemployment benefits and disutility of work). While the shock supposedly puts
an upward pressure on wages as it enhances the production value and intensifies
the disutility of work from the increased work hours, the rise in government
spending likewise boosts the shadow value of wealth, which mitigates thedisutility of labor (Kuo and Miyamoto, 2015). This model finds that the impact of
the latter is more pronounced.
The increase in interest rate follows the central bank’s reaction function as output
and inflation deviate from their steady state.3 The rise in interest rate not only
affects investments but also the firm’s hiring decisions through the lower
stochastic discount factor. There are two opposing factors at work here. On one
hand, the reduction in the discount factor diminishes the value of hiring a worker
thereby discouraging vacancy postings. On the other hand, the higher work hours
from the boost in government spending translates to enhanced labor productivity
thereby raising the value of the worker. (Kuo and Miyamoto, 2012) The outcome
depends on which of these countervailing factors will dominate. In this case, thebenefits from the enhanced value of a worker and the gains from pure economic
rent encourage firms to post vacancies. However in the longer term, firms seem toopt for expansion in the intensive margin vis-à-vis hiring new workers.

3 The relatively low financial depth in the Philippines, the competition between the government

and the private sector for the available funds puts pressure on the interest rate to increase (Tang,
Liu, and Cheung, 2010).

17

Figure 3: Impulse Responses to a Fiscal ShockLegend: Y is output, C is consumption, I is investment, ur is unemployment rate, h is hours
worked, v is vacancy, w is wage, pii is gross inflation and R is nominal interest rate

In summation, the model suggests that a fiscal expenditure shock leads to output
expansion, decrease in consumption, increase in vacancies, and fall in wage rates.
These factors contribute to the decline of the unemployment rate, which exhibitsa lagged response to the improvement in output and marks its lowest rate in thesecond quarter.4

5.2 Monetary Shock
Employing the same framework, this section simulates a one-period one standard
deviation negative monetary policy shock to analyze the impulse responses of
selected variables, especially unemployment, as shown in Figure 4. Following the
expansionary shock, the households increase their hours worked resulting in
output expansion, both variables peak on impact. The same is observed for
consumption and investment. However, unlike the usual hump-shape response of
output and investments in most literature, both variables experience a sharp
decline in the next period. This pattern suggests the lack of persistence likely on

4 Brooks (2002) examines the high unemployment in the Philippines using regression andcointegration analysis and finds a parallel conclusion that unemployment rate and real GDP
growth are negatively correlated.

18

account of the absence of some frictions. 5 It appears that since there are no
adjustment costs on capital, investment is able to instantaneously undertake thenecessary adjustment right after the shock to meet the higher future demand(Bouakez, Cardia, and Ruge-Murcia, 2002 and Christiano, Eichenbaum, and Evans,2005).
Figure 4: Impulse Responses to a Monetary Shock

Y

8
6

0.4

4

0.3

2

0.2

0

0.1

-2

10

20

30

h

15

C

0.5

0

20
10
0
10

20

30

v

30

-10

20

-1

5

10

-2

0

0

-3

10

20

30

w

0.8

-10

1

0.4

0.5

0.2

0
10

20

30

-0.5

20

30

pii

1.5

0.6

0

10

10

-4

20

30

20

30

20

30

ur

0

10

-5

I

30

10

R

0
-0.02
-0.04
-0.06
-0.08

10

20

30

-0.1

10

Legend: Y is output, C is consumption, I is investment, ur is unemployment rate, h is hours
worked, v is vacancy, w is wage, pii is gross inflation and R is nominal interest rate

As expected, the monetary shock lowers the nominal interest rates raising thestochastic discount factor thereby enhancing the marginal value of a worker to thefirms. The firms are encouraged to post vacancies today as the expectedcumulative benefit from the precluded hiring costs increases. Put in a different
way, the cost of hiring now is lower than the cost of posting vacancies in the future.
Hence, the expected lifetime profit for the firms rises providing the firms more
incentive to post vacancies at the current period, not to mention the improvementin the marginal revenue product following the output expansion. The increase invacancies means that more unemployed household members could get jobs,
5 Using Laplace’s method, Majuca (2011) concludes that the frictions critical to capturing the

dynamics of Philippine data are investment adjustment costs, habit formation, as well as price andwage rigidities.

19

hence, unemployment rate falls. Following a one period lag response from theimprovement in output, the unemployment rate dips the lowest in the second
quarter.
The improvement in the marginal productivity and the rise in work hours
translating to heightened disutility from working drive the wage rates up.
However, a sharp rise could be unlikely in the Philippine setting. According to
Cacnio (2012), wages in the country appear to have become relatively unreceptive
to output growth because of the oversupply of labor and the wage structure of thecountry resulting in substantial wage stickiness. The average annual labor force
growth rate from 2005 to 2013 averaged at 1.89 percent, as in Figure 5. Pitterle
and Zhang (2014) characterize the country’s labor force expansion as among thefastest in East Asia. Figure 6 plots the year-on-year growth rate of real minimum
wage in the National Capital Region (NCR). This hints that the model is unable tofully capture the wage condition in the country, probably due to the lack of wage
friction in the framework. The overall results of the calibrated model indicate that
expansionary monetary policy can potentially contribute to lowering theunemployment rate.
Figure 7: Real Minimum Wage,

Figure 5: Cross-country Labor Force
Expansion

Figure 6: Real
Minimum
National
Capital RegionWage, NCR
Year-on-Year
GrowthYear-on-Year Growth
RateRate

Figure 3: Cross-Country Labor Force Expansion Rate

12

60%

10

50%

8

40%
30%

6

20%

4

10%

2
0%
Q1 Q3 Q1 Q3 Q1 Q3 Q1 Q3 Q1 Q3 Q1 Q3 Q1 Q3 Q1 Q3 Q1 Q3 Q1 Q3 Q1 Q3

0
2005

2006

2007

2008

Indonesia
Philippines

2009

2010

Korea, Republic ofThailandSource: www.adb.org

2011

2012

Malaysia
Viet Nam

2013

-10%

2004

2005

2006

2007

2008

2009

Non-Agrculture

2010

2011

2012

2013

2014

Agriculture

Source: National Wages and Productivity
Commission, Author’s calculations

6 Conclusion
This paper is an antecedent application of the DSGE framework that incorporates
labor search theory to the Philippines to examine and analyze the impact of fiscal
and monetary shocks on output and unemployment. Unemployment in thePhilippines remains a challenge for policymakers as it stubbornly hovers at sevenpercent despite the remarkable economic performance in the recent years.
Results from the calibrated baseline model show that both expansionary fiscal andmonetary shocks lead to an expansion in output and an increase in vacancies,
translating to a decline in the unemployment rate. Moreover, a fiscal shock leads
to an increase in the hours worked but a fall in investment, consumption, and wage
20

rates. On the contrary, a negative monetary shock results in a rise in consumption,
investment, hours worked, and wage rates. Overall, the fiscal shock exhibits more
persistent effects on the economy and the labor market compared to the monetaryshock.
Based on the study, a number of drawbacks in the simplified model can be
identified. First, the need to incorporate more frictions to improve the overall
performance of the model, specifically, habit persistence, adjustment costs ofinvestment, and wage rigidity. This would generate more persistence in theimpulse response functions, especially in the monetary shock. Second, employ
actual data instead of stochastic simulation methods in generating the impulse
response functions. This enhancement would provide more insights on the
country’s unemployment condition. The nation’s unemployment is characterized
by a structural setback stemming from the disparity between the job
requirements set by businesses and the skills possessed by the available talentpool.6 Employing Bayesian estimation will determine matching efficiency of thelabor market and help shed light on the structural unemployment in the country.
Furthermore, since the model is primarily designed for formal sector employment,
the use of actual data from the NCR instead of the whole Philippines would offer amore precise assessment (i.e., relatively more standardized unemployment
opportunities). Lastly, the concurrent application of vector autoregression (VAR)
analysis will better assess the fit of the impulse response functions.
Nevertheless, the present model allows us to advance our understanding of thePhilippine unemployment dynamics and the effectiveness of policies instimulating growth and addressing the unemployment in the country. It paves theway for the exploration of related research on the area. Moreover, in light of thefindings of this paper on the positive impact of an expansionary monetary policy
shock on unemployment, the Central Bank could undertake further empiricalstudies on how its policies affect labor market conditions. The Central Bank may
find reason to reassess its conduct of monetary policy towards pursuing a more
active policy stance on supporting the general government in addressing thecountry’s unemployment condition. 7,8

5 The identified contributing factors include: 1) the cultural mindset of parents on particularprofessions, regardless of whether there is a demand for it in the economy; (2) the passing trendsof in demand professions; (3) the misperception of what is in demand coupled with herd mentality
among the market agents; and (4) the schools basing their course offerings on what they believe
the parents/students are keen on, thereby reinforcing the possibly misplaced expectations.
(Lorenciana, 2014, Habito, 2013, and Orillaza, 2014)
7 Lim (2006) similarly raises the issue of a more employment-sensitive monetary policy to help easelabor market conditions. Among the components of an alternative monetary policy that herecommends is the inclusion output and employment goals as part of the objectives of monetary
policy, citing the US Fed’s monetary policy approach wherein the Fed adjusts its policy rates toveering the economy to the direction it wants taking into account its multiple objectives.
8 Cacnio (2012) surmises that there is flattening of the Phillips curve in the country in the recent
decade. This implies that policy changes geared towards ameliorating unemployment will nottranslate to substantial upward pressure on inflation.

21

Appendix 1: Steady State Conditions

𝑛 =1−𝑈𝑢 = 1 − (1 − 𝑠) ∗ 𝑛
𝑣
𝜃=
𝑢
𝑚=𝑛∗𝑠
𝑚
𝑀 = 𝜉 (1−𝜉)
𝑢 𝑣
𝑚
𝑝=
𝑢
𝑚
𝑞=
𝑣
1
𝑟 𝐾 = − (1 − 𝛿)𝛽(𝜖 − 1)
𝑥=
𝜖
𝜋
𝑅=
𝛽
(1⁄

)

(𝛼−1)
𝑟𝐾
𝑘 = (𝑛 ∗ ℎ) ∗ ( )𝛼𝑥
𝑘=𝐾𝑦 = 𝑘 𝛼 ∗ (𝑛 ∗ ℎ)(1−𝛼)𝑦=Υ𝐼 = 𝛿𝐾
𝑔𝑜𝑣𝑒𝑟𝑛𝑚𝑒𝑛𝑡 𝑠𝑝𝑒𝑛𝑑𝑖𝑛𝑔
𝐺=
∗ Υ
𝐺𝐷𝑃
C = Υ − (𝐼 + 𝐺 + 𝜅𝑣)𝑤=

𝑥𝑦((1 − 𝛼) ∗ ( 𝑛 ) + (𝛽 ∗ (1 − 𝑠)) ∗ 𝜅𝜃) + (𝑧 +Φℎ(1+𝜇)∗)
𝜆(1 + 𝜇)ℎ𝜆 = 𝐶 −𝜎𝜆𝐾 = 𝜆Φ = (( 1 − 𝛼 ) 2 ∗𝑥𝑦𝜆) ∗ ( (1+𝜇) )𝑛ℎSteady-state values
Y
0.8015

C
0.4826I
0.2182ur
0.1461h0.3333v
0.1544w
1.4815pii
1.0000R
1.010122

Appendix 2: Log-linear Equilibrium Conditions

Labor Market𝑛̂𝑡 = (1 − 𝑠)𝑛̂𝑡−1 +

𝑚
𝑚
̂
𝑛 𝑡

̂𝑡 + 𝑛 𝑛̂𝑡 = 0
𝑈𝑈̂𝑡 + 𝜉𝑢̂𝑡 + (1 − 𝜉) 𝑣̂𝑡𝑚̂𝑡 = 𝑀𝑢 𝑢̂𝑡 = (𝑠 − 1) 𝑛 𝑛̂𝑡−1
𝜃̂𝑡 = 𝑣̂𝑡 + 𝑢̂𝑡𝑞̂𝑡 = 𝑚̂ 𝑡 − 𝑣̂𝑡𝑝̂ 𝑡 = 𝑚
̂ 𝑡 − 𝑢̂𝑡Households
𝜆̂𝑡 = 𝛾̂𝑡 − 𝜎 𝐶̂𝑡̂𝑡 = (1 − 𝛿) 𝐾
̂𝑡−1 + 𝐼 (𝐼̂𝑡 + 𝜓̂𝑡 )𝐾𝐾̂
𝜆̂𝑡 = 𝜆̂𝐾𝑡 + 𝜓𝑡𝜆̂𝑡 = 𝜆̂𝑡+1 + 𝑅̂𝑡+1 − 𝜋̂𝑡+1
𝐾
𝐾 ̂
̂𝐾
𝜆̂𝐾
𝑡 = 𝛽𝑟 (𝜆𝑡+1 + 𝑟̂𝑡+1 ) + 𝛽(1 − 𝛿)𝜆𝑡+1

Intermediate Goods Firms
𝑦̂𝑡 = 𝐴̂𝑡 + 𝛼𝑘̂𝑡 + (1 − 𝛼)𝑛̂𝑡 ℎ̂𝑡𝑟̂𝑡𝐾 = 𝑥̂𝑡 + 𝑦̂𝑡 − 𝑘̂𝑡−𝜅𝑥𝑦(𝑥̂ + 𝑦̂𝑡 − 𝑛̂𝑡 ) + 𝑤ℎ (𝑤𝑞̂𝑡 = (1 − 𝛼)
̂ 𝑡 + ℎ̂𝑡 ) +𝑞𝑛 𝑡𝜅̂ 𝑡 + 𝑞̂𝑡+1 )𝛽 (1 − 𝑠) 𝑞 (𝜆̂𝑡+1 − 𝜆̂Retailers23𝜄𝜋̂𝑡 = (1+𝛽𝛽𝜄)𝜋̂𝑡−1 + (1+𝛽𝜄)𝜋̂𝑡+1 +

(1−𝛽𝜑)(1−𝜑)𝜑(1+ 𝛽𝜄)𝑥̂𝑡 + 𝜖̂𝑡

Wages and Hours Bargaining𝑤ℎ (𝑤̂ 𝑡 + ℎ̂𝑡 ) = 𝜂 [(1 − 𝛼)𝑥𝑦𝑛(𝑥̂𝑡 + 𝑦̂𝑡 − 𝑛̂𝑡 ) + 𝛽(1 − 𝑠)𝜅𝜃
̂ 𝑡 + 𝜃̂𝑡+1 )(𝜆̂𝑡+1 − 𝜆̂]Φ𝜒 ℎ(1+𝜇)̂𝑡 ]+ (1 − 𝜂 )[𝜒̂ 𝑡 + (1 + 𝜇)ℎ̂𝑡 − 𝜆̂
1+ 𝜇 𝜆̂𝑡𝑥̂𝑡 + 𝑦̂𝑡 − 𝑛̂𝑡 − ℎ̂𝑡 = 𝜒̂ 𝑡 + 𝜇 ℎ̂𝑡 − 𝜆̂Monetary Policŷ𝑡 ) − 𝜁̂𝑚𝑝,𝑡𝑅̂𝑡 = 𝜌𝑅 𝑅̂𝑡−1 + (1 − 𝜌𝑅 ) (𝜙𝜋 𝜋̂𝑡 + 𝜙Υ Υ
Closing the Model̂𝑡𝑦̂𝑡 = Υ̂𝑡𝑘̂𝑡 = K̂𝑡 = 𝐶𝐶̂𝑡 + 𝐼𝐼̂𝑡 + 𝐺𝐺̂𝑡 + 𝜅𝑣𝑣̂𝑡
ΥΥ
Shocks𝜁̂𝑚𝑝,𝑡 = 𝜀̂𝜁̂ ,𝑡𝐺̂𝑡 = 𝜌𝐺 𝐺̂𝑡−1 + 𝜀̂𝐺,𝑡24

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