Remittances, Monetary Policy, and the Dutch Disease：A
Case from the Philippines

Fujiwara Manato

Graduate School of Economics, Hosei University
2-17-, Fujimi, Chiyoda-ku, Tokyo, Japan
E-mail: manato.fujiwara.8b@stu.hosei.ac.jp

Abstract
This study analyzes the Dutch disease effect of remittances using a dynamic stochastic general equilibrium (DSGE) model ofa small open economy. The Dutch disease effect is known in remittance literature as a negative side effect of remittances, where
the massive inflow of remittances leads to higher domestic prices and real exchange rate appreciation, hurting the tradable
sector. However, it is widely known that the effect varies across countries and regions, and thus, there is room for further
discussion on what factors can exacerbate the Dutch disease effect of remittances. Exchange rate regimes can affect realexchange rate fluctuations, which may make a difference in the Dutch disease effect of remittances, but few previous studies
consider the relationship between exchange rate regimes and remittances. To fill this gap, this study constructs a two-agent,
two-sector DSGE model in which the central bank emphasizes exchange rate stability. Calibrated from Philippine data, thisstudy finds that under a floating exchange rate regime, an appreciation of the nominal exchange rate and upward pressure on
prices can lead to a contraction of the tradable sector, leading to Dutch disease, regardless of the income effect of remittances.
This study also shows that the tradable sector can expand under a fixed exchange rate regime without the income effect ofremittances. However, when the income effect is sufficiently strong, labor supply to the tradable sector declines, leading to acontraction of tradable output and Dutch disease through resource movement effects. These results suggest that different
exchange rate regimes alone may not prevent resource movement effects and that the income effect of remittances may be a
key determinant in the dynamics of Dutch disease. In the Philippines, both the exchange rate and income effect channels may
amplify the Dutch disease effect of remittances.

Keywords: Remittances, Dutch Disease, tradable sector, Exchange Rate Regime
JEL Classification: F22, F24, F41, O1

1. Introduction
In recent years, the inflow of migrant remittances (or worker remittances, herein referred to as remittances) todeveloping and emerging economies has been increasing and their macroeconomic impact has been attracting attention.
While the benefits of increased remittances, such as improved balance of payments, consumption smoothing effects, andpoverty reduction, have been significant, negative aspects such as the "Dutch disease" have also been identified, in which
remittances push up prices in recipient countries, appreciating the real exchange rate and hindering the development of the
tradable goods sector. Although various empirical and theoretical studies have been conducted on the Dutch Disease effectof remittances, it is widely known that there are large differences across countries and regions (Anwar, et al, 2022), and it
is highly controversial what factors are more likely to be associated with the Dutch disease effect.
The Dutch disease effect of remittances is mainly analyzed in terms of the real exchange rate, but changes in thenominal exchange rate are also important by the definition of the real exchange rate. Since it is generally confirmed thatthe exchange rate overshoots in the short and long run due, for instance, to the Balassa-Samuelson effect, where thedifferences in productivity in the non-tradable sector can result in the overshoot (Mark, 2000, and Betts and Devereux,2000), the impact of remittances on the real exchange rate can depend on the degree to which countries are affected by its
pass-through. In particular, the degree to which countries can tolerate nominal exchange rate fluctuations is directly
dependent on the exchange rate regime of each country, and it is possible that differences in exchange rate regimes affectreal exchange rate movements, potentially leading to differences in the Dutch disease effect on remittances across countries.
Figure 1 shows the relationship between the size of remittances and the different types of exchange rate regimes
based on the IMF's de facto classification of exchange arrangements. First, we see that remittance inflows are relatively
small in countries that are viewed as ex post perfect free-floating exchange rate systems, whereas remittance-to-GDP ratios
are larger in countries with stronger policies that peg their currencies to fluctuations in foreign currencies. Singer (2010)shows that remittances raise the possibility of the central bank pursuing nominal exchange rate stability, rather than pricestability. Thus, it can be said that there is a non-negligible relationship between exchange rate regimes and remittances.
Figure1: Relationship between the size of the remittances and exchange rate regimes2%Remittance to GDP (2022)

60
50
40

30
20
10
0
0

Free Floating

1

Soft Peg

2

Hard Peg

3

Note: The above classification is based on the IMF's de facto classification of exchange rate
arrangements, as of April 30, 2022. Soft Peg is counted as "floating", "other managed arrangement","pegged exchange rate within horizontal", and "crawl-like arrangement". Hard Peg is defined as"crawling peg", "stabilized arrangement", "conventional peg", "currency board", and "no separate
legal tender". Free Floating is counted if the country is classified as "free floating".

Nevertheless, few previous studies consider exchange rate regimes, and the empirical results are inconclusive.
While some studies show that a freely floating exchange rate regime helps dampen the appreciation of the real exchange
rate due to remittances (Hien et al. (2020) and Combes et al. (2012)), others show that a fixed exchange rate regime restrains
the degree of real exchange rate appreciation and helps minimize the Dutch disease effect of remittances (Mandelman,2013). Despite a number of studies analyzing the Dutch disease of remittances using a dynamic stochastic generalequilibrium (DSGE) model framework (Acosta, et al, 2009, Bahadir et al, 2018, and Lim and Khan, 2022), few studies
have focused on the relationship between exchange rate regimes and remittances. Mandelman (2013) and Lartey (2015),
in this regard, build a DSGE model with the exchange rate arrangements and analyze the relationship between remittancesand nominal exchange rate fluctuations. However, the former uses a single-sector formulation, which limits the discussionof resource movement effects. Because the ultimate objective is to investigate whether remittances hinder the developmentof the tradable sector, it is crucial to examine the dynamics of both the real exchange rate and the structural transformation,
as in Acosta et al. (2009). The latter study also abstracts from important aspects of remittances such as household
heterogeneity, the presence or absence of income effects, and the countercyclical nature of remittances.
To fill these gaps, this study constructs a DSGE model incorporating a two-household, two-sector framework thatconsiders exchange rate regimes and analyzes the economic dynamics caused by remittance shocks. Specifically, the model
extends Mandelman (2013) to include two sectors, allowing for a dynamic analysis of resource movement effects andexchange rate regimes. Since the income effect of remittances on labor is crucial to the model's dynamics, this study
compares the differences using Greenwood, Hercowitz, and Huffman (GHH) preferences, which have no income effect,3and a constant relative risk aversion (CRRA) preference with income effects.
Remittance-receiving countries, including the Philippines, tend to have large informal economies, as Chatterjee
and Turnovsky (2018) show. Despite the lack of access to banks (and international capital markets), the informal economy
often serves as a shock absorber for domestic economic shocks, as workers migrate abroad and remit earnings back homeduring times of economic hardships. To incorporate such self-insurance effects, this model introduces 'hand-to-mouth'
households that face liquidity constraints and receive countercyclical remittances. However, unlike Mandelman (2013), in
which only liquidity-constrained households receive remittances, this model also considers households that migrate as
skilled labor and remit through formal banking channels. Thus, in our model, both hand-to-mouth and Ricardian householdswith access to banks and bond markets receive remittances.
We use Philippine data and the Bayesian method to estimate some of the parameters that are deemed highly datadependent, such as the Taylor rule parameters that determine the exchange rate regime and parameters related tocountercyclical remittances. The Philippines is one of the most remittance-dependent countries in Southeast Asia, with aremittance-to-GDP ratio of approximately 10 percent by the end of 2022, and its impact on the macroeconomy has received
considerable attention. As Figure 2 shows, the overall size of remittances has generally been on an upward trend, and theeconomic structure has shifted more toward services during this period. As Vu (2022) argues, the Philippines has shown
signs of 'premature deindustrialization,' with an early shift from industry to services. If remittances caused the Dutch disease
effect, this could accelerate the process of deindustrialization. Moreover, the informal economy in the Philippines is
estimated to account for about 35% of the GDP in the Philippines as of 2017 (Medina and Schneider, 2019), and Yang andChoi (2007) note that remittances in the Philippines serve as self-insurance for domestic households. Therefore, thePhilippines is considered to align well with our model setup.
Figure2

Remittances and shift in economic structure

4

(%)
14

2.5

12
2
10
8

1.5

6

1

4
0.5
2
0

1977
1979
1981
1983
1985
1987
1989
1991
1993
1995
1997
1999
2001
2003
2005
2007
2009
2011
2013
2015
2017
2019
2021

0

Remittance to GDP (LHS)

Service to Industry (RHS)

Source: World Development Indicators

The main results are as follows. First, tradable output expands when there is no income effect from remittances,and the central bank prevents the appreciation of the nominal exchange rate against remittance inflows. Under a fixedexchange rate regime, interest rate cuts spurred by the remittance increase not only prevent the appreciation of the realexchange rate, but also encourage investment, which contributes to capital accumulation in the tradable sector. However,even in the absence of the income effect, the free-floating regime induces an appreciation of the real exchange rate and areduction in exports, as well as a decline in investment due to monetary tightening, resulting in a contraction of the tradable
sector. This contrasts with the results of Acosta et al. (2009), where tradable output expands slightly because of the removalof labor supply constraints in the absence of income effects, suggesting that different exchange rate regimes may lead todifferent resource movement effects. However, this study also finds that even when the impact of exchange rate appreciation
is mitigated by interest rate cuts, the income effect of remittances causes the labor supply in the tradable sector to shrink,which in turn results in the contraction of tradable output. In summary, although the exchange rate regime may lead todifferent effects on real exchange rates, the absence of the income effect of remittances may be a key determinant inpreventing the tradable sector from contracting.
The rest of the paper is organized as follows: In Section 2, we review previous studies on the remittance and Dutch
disease effects of exchange rate regimes, and in Section 3, we present the model derivation. In Section 4, we present theestimation methodology and analysis of model dynamics using Bayesian impulse response functions (IRFs). We thendiscuss the case of the Philippines based on the model simulations and empirical findings in Section 5. Finally, Section 6
synthesizes the results and draws the conclusions.

52. Literature Review
In an empirical study that takes into account the exchange rate regime with respect to the Dutch disease effect ofremittances, Ball et al. (2012), for example, construct a panel vector autoregressive (VAR) model with fixed and floatingexchange rate regimes and examine the differences in response to remittance shocks. They show that the remittance shock
appreciates the real exchange rate regardless of the exchange rate regime but increases inflation only under a fixed exchange
rate regime. The fact that under both regimes, the real exchange rate appreciates might reflect the difference in the nominal
exchange rate. Lartey et al. (2012) use Generalized Method of Moments (GMM) estimators to address potential
endogeneity issues and show that remittances induce shifts in economic structure to non-tradable sectors, known as theresource movement effect, even after controlling for the effects of empirically relevant variables. They show that incountries with fixed nominal exchange rates, remittances reduce the size of the tradable goods sector to a greater extent.
However, these empirical studies are essentially reduced-form estimates and do not consider dynamic effects. Hien, et al(2020) use 32 Asian developing countries to investigate the impact of remittances on the real exchange rate and show thatthe floating exchange rate regime helps minimize real exchange rate appreciation. Similar results were reported by Combes
et al. (2012).
Regarding the analysis based on a DSGE model framework, Acosta, et al (2009) construct a DSGE model toanalyze the Dutch disease effect of remittances. The model simulations and Bayesian VAR analysis using data for El
Salvador show that an exogenous remittance shock can lead to an appreciation of the real exchange rate and a contractionof the tradable goods sector. They also show that the income effect of remittances, where remittances contribute to a
reduction in working hours for remittance-receiving households, intensifies the Dutch disease effect through the resource
movement effect. Mandelman (2013) builds a DSGE model with a central bank that focuses on nominal exchange ratestability to analyze the impact of remittances and monetary policy. However, as argued above, it is a one-sector formulationand thus does not analyze the resource movement effect between the tradable and non-tradable goods sectors, a key
mechanism of Dutch disease. In a recent study, Bahadir et al. (2018) show that households facing borrowing constraints
increase investment in response to the remittance shock, while Lim and Khan (2022) show that endogenous migration
abroad under similar conditions is associated with a reduced labor supply in the tradable goods sector, thus potentiallyintensifying the Dutch disease through resource movements effects. However, these studies do not consider differences inexchange rate regimes. Lartey (2015) analyzes the resource movement effect based on the two-sector DSGE model andshows that Dutch disease occurs only under a fixed exchange rate regime. However, this study lacks importantcharacteristics of remittances, such as household heterogeneity, the presence or absence of income effects, and the6countercyclical nature of remittances.
Bayangos and Jansen (2011) examine the macroeconomic impact of remittances in the Philippines. Not only dothey find that an inflow of remittances leads to appreciation and a decline in tradable output, but they also highlight theimportance of accounting for labor emigration. They show that the decline in the labor force induced by remittance inflow
has a greater impact on the decline in tradable output than through the real exchange rate channel. Using a structural VAR
model, Vu (2023) shows that an increase in remittances contributes to a lower labor force participation rate and appreciationof the real exchange rate in the Philippines. Moreover, he shows not only that the share of value added of the tradable sector
in that of the service sector declines against the remittance shock but also that the absolute value added of the tradable
sector shrinks after controlling for world industrial output.

3. The model
3-1: Households
3-1-1: GHH preference
There is a continuum of infinitely lived households. A fraction 1 − 𝜆 of households has access to the international
capital market (or a formal banking channel), which is referred to as “Ricardian (or optimizing).” The remaining fraction
𝜆 of households neither own their assets nor hold any liabilities and use all of their labor income and remittances for
consumption in the current period. We refer to this subset of households as “hand-to-mouth households”. In the case of
GHH preference specification, Ricardian households have the following utility and budget constraints:

1−𝜎[𝐶𝑅,𝑡 − 𝜏∞𝐸𝑜 ∑ 𝛽

𝑡

−1

1−𝜎

𝑡=0

{

𝐿1+𝜈
𝑅,𝑡
]
1+𝜈

[

]}

subject to𝐶𝑅,𝑡 +

𝑣𝑡 𝑥𝑡+1(1 + 𝑖𝑡 )𝐵𝐻,𝑡−1 𝑆𝑡 (1 + 𝑟)𝐵𝐹,𝑡++𝑃𝑡 (1 − 𝜆)𝑃𝑡 (1 − 𝜆)𝑃𝑡 (1 − 𝜆)=(𝑉𝑡 + 𝐷𝑡 )𝑥𝑡 𝑊𝑡 𝐿𝑅,𝑡1
𝑆𝑡 𝐵𝐹,𝑡 𝑆𝑡 𝜑𝐵
𝐵𝐻,𝑡
𝑆𝑡
2
+
+
{
−
(𝐵𝐹,𝑡 − 𝐵̅ ) } ++ (𝛯𝑐 + 𝛯𝑡𝑑 )𝑃𝑡 (1 − 𝜆)𝑃𝑡
1 − 𝜆 𝑃𝑡
𝑃𝑡 2
𝑃𝑡 (1 − 𝜆) 𝑃𝑡 𝑡

Henceforth, we use “R” subscript to denote Ricardian households’ variables. 𝐶𝑅,𝑡 and 𝐿𝑅,𝑡 are the consumption
and labor supply of Ricardian households, 𝑥𝑡 is the number of shares purchased from firms in the tradable sector, 𝑊𝑡 is
nominal wages, 𝑉𝑡 and 𝐷𝑡 are the value of firms in the tradable goods sector and the dividend payments issued by tradable7

sector firms, respectively. 𝑃𝑡 and 𝑃𝐹,𝑡 are the consumer price index and the foreign consumer price index in units of foreign
currency, respectively; 𝐵𝐹,𝑡 and 𝐵𝐻,𝑡 are the amount of external debt held in foreign currency and of domestic debt held in
local currency due in period 𝑡, and r and 𝑖𝑡 is the level of world interest rate and domestic interest rate, respectively. We
𝐵2
𝑆 𝜑assume an adjustment cost of holding debt 𝑃𝑡 2 (𝐵𝐹,𝑡 − 𝐵̅) where 𝜑𝐵 and 𝐵̅ are parameters that determine the cost of𝑡

holding foreign debt and the steady-state debt level, respectively. 𝑆𝑡 is the nominal exchange rate representing one homecurrency per foreign currency unit, 𝛯𝑡𝑐 is the exogenous remittances that follow an AR (1) stochastic process, and 𝛯𝑡𝑑 isanother form of remittance that captures the countercyclical nature of remittances.
Given a Lagrangian multiplier 𝛬𝑅,𝑡 , the optimality conditions for 𝐶𝑅,𝑡 , 𝐿𝑅,𝑡 , 𝐵𝐹,𝑡 , 𝑥𝑡+1 , and 𝐵𝐻,𝑡 are as follows:−𝜎𝛬𝑅,𝑡 = [𝐶𝑅,𝑡 − 𝜏

(1)

𝐿1+𝜈
𝑅,𝑡
]
1+𝜈

−𝜎

𝜏𝐿𝜈𝑅,𝑡 = 𝛬𝑅,𝑡

(2)

[𝐶𝑅,𝑡 − 𝜏

(3)

1 − 𝜑𝐵 (𝐵𝐹,𝑡 − 𝐵̅) = 𝛽∞

𝑉𝑡 = ∑ 𝛽 𝑖 𝐸𝑡 [

(4)

𝑖=0

(5)

1=𝛽

𝐿1+𝜈
𝑅,𝑡
]
1+𝜈

𝑊𝑡
𝑃𝑡

𝛬𝑅,𝑡+1 𝑆𝑡+1 𝑃𝑡(1 + 𝑟)𝛬𝑅,𝑡 𝑆𝑡 𝑃𝑡+1

𝛬𝑅,𝑡+𝑖 𝑃𝑡
𝐷 ].
𝛬𝑅,𝑡 𝑃𝑡+𝑖 𝑡+𝑖

𝛬𝑅,𝑡+1 𝑃𝑡(1 + 𝑖𝑡+1 )𝛬𝑅,𝑡 𝑃𝑡+1

Using (3) and (5), we obtain the following uncovered interest parity (UIP) condition, where the nominal exchange
rate is adjusted given an interest rate differential.

(1 + 𝑖𝑡 ) = (1 + 𝑟)

𝑆𝑡+1̅)
+ (1 + 𝑖𝑡 )𝜑𝐵 (𝐵𝐹,𝑡 − 𝐵
𝑆𝑡

The hand-to-mouth households (denoted with “hm” subscript) have the following utility function and budget
constraints
1−𝜎[𝐶ℎ𝑚,𝑡 − 𝜏∞

𝐸𝑜 ∑ 𝛽 𝑡

−1

1−𝜎

𝑡=0

{

𝐿1+𝜈
ℎ𝑚,𝑡
]
1+𝜈

[

]}

subject to8𝜆 𝐶ℎ𝑚,𝑡 = 𝜆

𝑊𝑡 𝐿ℎ𝑚, 𝑡𝑆𝑡+ 𝜆 (Ξtc + Ξtd ).
𝑃𝑡
𝑃𝑡

Eliminating 𝛬𝑅,𝑡 from (1) and (2), we obtain the following equation for the marginal rate of substitution between
consumption and leisure (labor):
𝜏𝐿𝜈𝑅,𝑡 =𝑊𝑡
𝑃𝑡

In the case of the GHH-type utility function, as shown above, consumption is eliminated from the equation
determining labor supply. Thus, the labor supply of each household is determined solely by the level of real wages, aspecification that eliminates the income effect.

3-1-2: CRRA preference
The utility function and budget constraint for Ricardian households in the CRRA-type utility function are specified
as follows:
∞

1−𝜎
𝐶𝑅,𝑡
𝐿1+𝜈
𝑅,𝑡
]}
𝐸𝑜 {∑ 𝛽 𝑡 [
−𝜏
1−𝜎
1+𝜈
𝑡=0

subject to𝑣 𝑥(1+𝑖𝑡 )𝐵𝐻,𝑡−1𝑡𝑃𝑡(1−𝜆)𝑡+1
𝐶𝑅,𝑡 + 𝑃 𝑡(1−𝜆)+𝑆 (1+𝑟)𝐵(𝑉 +𝐷 )𝑥𝑡 𝑡
+ 𝑡𝑃 (1−𝜆)𝐹,𝑡 = 𝑃𝑡 (1−𝜆)+𝑡𝑊𝑡 𝐿𝑅,𝑡

𝑡

𝑃𝑡

1

𝑆 𝐵

𝑆 𝜑𝐵

2

𝐵

𝑆

𝐻,𝑡
+ 1−𝜆 { 𝑡𝑃 𝐹,𝑡 − 𝑃𝑡 2 (𝐵𝐹,𝑡 − 𝐵̅) } + 𝑃 (1−𝜆)+ 𝑃𝑡 (𝛯𝑡𝑐 + 𝛯𝑡𝑑 )
𝑡

𝑡

𝑡

𝑡

In addition, hand-to-mouth households’ specification is :
∞

1−𝜎
𝐶ℎ𝑚,𝑡
𝐿1+𝜈
ℎ𝑚,𝑡
]}
𝐸𝑜 {∑ 𝛽 𝑡 [
−𝜏
1−𝜎
1+𝜈
𝑡=0

subject to

𝜆 𝐶ℎ𝑚,𝑡 = 𝜆

𝑊𝑡 𝐿ℎ𝑚, 𝑡𝑆𝑡+ 𝜆 (Ξtc + Ξtd ).
𝑃𝑡
𝑃𝑡

The only differences in the first-order conditions between the GHH and CRRA preferences are with regard to
consumption and labor decisions, as follows:−𝜎𝜏𝐿𝜈ℎ𝑚,𝑡 = 𝐶ℎ𝑚,𝑡

𝑊𝑡
𝑃𝑡

In the case of a CRRA-type utility function in which consumption and labor are separable, given 𝜈 > 0 and 𝜎 >0, there is a trade-off between consumption and labor choices. An increase in remittances leads to higher consumption, but
simultaneously reduces labor supply due to the income effect. Note that if 𝜆 = 0 in each of the preferences can be attributed
to the representative household specification, where all households have access to an international capital market.

93-2: Consumption composites
Consumption is composed of four different types of goods: tradable consumption 𝐶𝑇,𝑡 , non-tradable consumption,
𝐶𝑁,𝑡 with tradable consumption being both domestically produced goods 𝐶𝐻,𝑡 and foreign goods 𝐶𝐹,𝑡 . We assume thefollowing CES-type consumer good basket:
1

𝜌𝑐−1

1

𝜌𝑐−1

𝜌𝑐

𝐶𝑡 = [(𝛾𝑐 )𝜌𝑐 (𝐶𝑁,𝑡 ) 𝜌𝑐 + (1 − 𝛾𝑐 )𝜌𝑐 (𝐶𝑇,𝑡 ) 𝜌𝑐 ]𝜌𝑐−1
1

𝜌ℎ−1

1

𝜌ℎ−1

𝜌ℎ

𝐶𝑇,𝑡 = [(𝛾ℎ )𝜌ℎ (𝐶𝐻,𝑡 ) 𝜌ℎ + (1 − 𝛾ℎ )𝜌ℎ (𝐶𝐹,𝑡 ) 𝜌ℎ ]𝜌ℎ−1
𝛾𝑐 𝑎𝑛𝑑 𝛾ℎ ∈ [0,1] are the shares of non-tradables in total consumption and home goods in tradable consumption,
respectively; 𝜌𝑐 > 0 and 𝜌ℎ > 0 represent the elasticity of substitution. By minimizing the nominal expenditure, subject
to the above baskets of consumer goods, we obtain the demand curve for each type of consumption goods as follows:
𝑃𝑁,𝑡 −𝜌
) 𝑐 𝐶𝑡𝑃𝑡(8)

𝐶𝑁,𝑡 = 𝛾𝑐 ((9)

𝐶𝑇,𝑡 = (1 − 𝛾𝑐 )((10)

𝐶𝐻,𝑡 = 𝛾ℎ (

1
𝑃𝐶𝑇,𝑡

𝐶𝐹,𝑡 = (1 − 𝛾ℎ )((11)

𝑃𝑇,𝑡 −𝜌
) 𝑐 𝐶𝑡𝑃𝑡)−𝜌ℎ 𝐶𝑇,𝑡

𝑃𝐶𝐹,𝑡 −𝜌) ℎ 𝐶𝑇,𝑡𝑃𝐶𝑇,𝑡where 𝑃𝑁,𝑡 , 𝑃𝑇,𝑡 and 𝑃𝐶𝐹,𝑡 are the prices of non-tradable goods, tradable consumption goods, and foreign tradable
consumption goods, respectively. The price of the domestic tradable consumption good was set to one for the numeraire.
Substituting these conditions into the original CES-type consumption basket yields the following prices.

1

(12)

𝑃𝑡 = [𝛾𝑐 (𝑃𝑁,𝑡 )1−𝜌𝑐 + (1 − 𝛾𝑐 )(𝑃𝐶𝑇,𝑡 )1−𝜌𝑐 ]1−𝜌𝑐(13)

𝑃𝐶𝑇,𝑡 = [𝛾ℎ + (1 − 𝛾ℎ )(𝑃𝐶𝐹,𝑡 )1−𝜌ℎ ]1−𝜌ℎ13-3: Firms
There are two firm sectors: tradable and non-tradable. Tradable-goods firms are further divided into investment

10and production units, where the investment unit selects the optimal basket of domestic and foreign investment goods
financed by remittances. Given the composition of aggregate investment determined by the investment unit, the production
unit produces tradable goods based on constant returns on scale technology. Non-tradable firms are divided into
intermediate- and final-goods producers. Monopolistically competitive firms produce non-tradable intermediate goods.

3-3-1: Tradable goods sector: investment unit
The investment unit in the tradable goods sector combines domestic investment goods (𝐼𝐻,𝑡 ) and investment goods
imported from abroad (𝐼𝐹,𝑡 ) to produce aggregate investments (𝐼𝑡 ), as follows:
𝜌𝑖−1

1

1

𝜌𝑖−1

𝜌𝑖

𝐼𝑡 = [(𝛾𝑖 )𝜌𝑖 (𝐼𝐻,𝑡 ) 𝜌𝑖 + (1 − 𝛾𝑖 )𝜌𝑖 (𝐼𝐹,𝑡 ) 𝜌𝑖 ]𝜌𝑖−1 .
The optimization yields demand functions for each of the investment goods demands followingly:
1 −𝜌
) 𝑖 𝐼𝑡𝑃𝐼,𝑡(14)

𝐼𝐻,𝑡 = 𝛾𝑖 ((15)

𝐼𝐹,𝑡 = (1 − 𝛾𝑖 )(𝑃𝐼𝐹,𝑡 −𝜌) 𝑖 𝐼𝑡𝑃𝐼,𝑡The unit cost function for 𝐼𝑡 is then expressed as follows;
1

𝑃𝐼,𝑡 = [𝛾𝑖 + (1 − 𝛾𝑖 )(𝑃𝐼𝐹,𝑡 )1−𝜌𝑖 ]1−𝜌𝑖(16)

We assume the price of the domestic tradable good to be 1 as the numeraire.

3-3-2: Tradable goods sector: production unit
In the production unit, tradable good 𝑌𝑇,𝑡 is produced by the following constant returns to scale technology 𝑌𝑇,𝑡 =𝐴𝑇𝑡 𝐾𝑡𝛼 𝐿1−𝛼
. Capital 𝐾𝑡 accumulates as in the following dynamic equation: 𝐾𝑡+1 = (1 − 𝛿 )𝐾𝑡 + 𝐼𝑡 , where 𝛿 is the𝑡depreciation rate and the amount of investment is obtained by the investment unit. A tradable good firm maximizes thepresent discounted value of dividends as follows:∞𝛬𝑅,𝑠 𝑃0
𝐸𝑡 ∑ 𝛽 𝑠 [𝐷 ] 𝑓𝑜𝑟 𝑠 = 𝑡, 𝑡 + 1, 𝑡 + 2 …
𝛬R,0 𝑃𝑠 𝑠
𝑠=𝑡

subject to𝜂 𝐼𝑠
𝐷𝑠 = 𝑌𝑇,𝑠 − 𝑃𝐼,𝑠 (𝐼𝑠 + ( − 𝛿)2 𝐾𝑠 ) − 𝑊𝑠 𝐿 𝑇,𝑠
2 𝐾𝑠

11

(17)

𝐾𝑡+1 = (1 − 𝛿 )𝐾𝑡 + 𝐼𝑡

(18)

𝑌𝑇,𝑠 = 𝐴𝑇𝑠 𝐾𝑠𝛼 𝐿1−𝛼
𝑠
𝛬

𝑃

𝜂 𝐼

𝑠 𝑅,𝑠 0where ∑∞
is a stochastic discount factor and the installation cost of capital 2 (𝐾𝑠 − 𝛿)2 𝐾𝑠 is incurred as a unit of𝑠=𝑡 𝛽 𝛬
𝑃
𝑅,0

𝑠

𝑠

capital increases, where 𝜂 determines the installation cost. The optimality conditions for 𝐾𝑡+1 , 𝐼𝑡 , 𝐿 𝑇,𝑡 are:(19)

𝑄𝑡 = 𝛽𝛬𝑅,𝑡+1 𝑃𝑡
𝑌𝑡+1𝜂 𝐼𝑡+1𝐼𝑡+1
𝐼𝑡+1{𝛼− 𝑃𝐼,𝑡+1 [ (− 𝛿)2 − 𝜂 (− 𝛿)] + 𝑄𝑡+1 (1 − 𝛿)}𝛬𝑅,𝑡 𝑃𝑡+1 𝐾𝑡+1
2 𝐾𝑡+1
𝐾𝑡+1
𝐾𝑡+1

(20)

𝑄𝑡 = 𝑃𝐼,𝑡 {1 + 𝜂 ((21)(1 − 𝛼 )

𝐼𝑡
− 𝛿)}
𝐾𝑡

𝑌𝑇,𝑡
= 𝑊𝑡
𝐿 𝑇,𝑡

where 𝑄𝑡 is a Lagrangian multiplier.

3-3-3: Non-Tradable Goods Sector
Final goods producers
The non-tradable final good is produced with a continuum of varieties of intermediate non-tradable inputs using
the following technology:
1

𝑌𝑁,𝑡 = [∫ (𝑌𝑁𝑖,𝑡

𝜃
𝜃−1
𝜃−1
𝜃
)
𝑑𝑖] ,

0

where 𝑌𝑁,𝑡 denotes the tradable final output, 𝑌𝑁𝑖,𝑡 denotes the quantity of intermediate goods of firm 𝑖 ∈ [0, 1] used in the

final goods production, and 𝜃 > 1 denotes the elasticity of substitution across a variety of goods. Profit maximization
subject to the above production technology yields the demand curve for final goods producers as follows:
𝑃𝑁𝑖,𝑡
𝑌𝑁𝑖,𝑡 = (
)
𝑃𝑁,𝑡

−𝜃

𝑌𝑁,𝑡 .

Using this expression to eliminate 𝑌𝑁𝑖,𝑡 from production technology, the price of the final non-tradable good interms of the price of intermediate goods is given as follows:11−𝜃𝑃𝑁,𝑡 = [∫ (𝑃𝑁𝑖,𝑡 )
0

12

1
1−𝜃

𝑑𝑖 ]

.

Intermediate goods producers
Non-tradable intermediate goods are produced by monopolistically competitive firms indexed by 𝑖 ∈ [0, 1]. Firm𝑖, facing the demand function given by the final goods producer, maximizes the present discounted value of profit
Π𝑖,𝑡 as follows:∞𝐸0 ∑ 𝛽 𝑡 [𝑡=0subject to𝛬𝑡Π ]𝛬0 𝑖,𝑡2

Π𝑖,𝑡 =

𝑃𝑁𝑖,𝑡𝑊𝑡
𝜂𝑝𝑛 1 + 𝜋𝑡𝑛
𝑌𝑁𝑖,𝑡 −
𝐿𝑁𝑖,𝑡 −(
− 1) 𝑌𝑁,𝑡
𝑛
𝑃𝑁,𝑡
𝑃𝑁,𝑡
2 1 + 𝜋𝑠𝑠
𝑌𝑁𝑖,𝑡 = 𝐴𝑁𝑇
𝑡𝑖 𝐿𝑁𝑖,𝑡
𝑌𝑁𝑖,𝑡 = (

where

𝜂𝑝𝑛
2

(

1+𝜋𝑡𝑛
𝑛
1+𝜋𝑠𝑠

𝑃𝑁𝑖,𝑡
)
𝑃𝑁,𝑡

−𝜃

𝑌𝑁,𝑡

2

− 1) 𝑌𝑁,𝑡 represents the Rotemberg price adjustment cost, 𝜂𝑝𝑛 denotes the parameter that adjusts the𝑃𝑛price adjustment cost. We define 1 + 𝜋𝑡𝑛 = 𝑃 𝑁,𝑡 and 𝜋𝑠𝑠
as the steady-state level of the non-tradable inflation rate. 𝐴𝑁𝑇
𝑡𝑖 is
𝑁,𝑡−1

is an exogenous stochastic productivity shock. Profit maximization yields the following optimality conditions for 𝐿𝑁𝑖,𝑡 and𝑃𝑁𝑖,𝑡 respectively;
𝜕ℒ
𝜕𝐿𝑁𝑖,𝑡

𝑀𝐶𝑡 𝐴𝑁𝑇𝑡𝑖 =𝑃(1 − 𝜃) ( 𝑁𝑖,𝑡 )𝑃𝑁,𝑡𝜕ℒ
𝜕𝑃𝑁𝑖,𝑡

−𝜃

−

𝑊𝑡
𝑃𝑁,𝑡

𝜂𝑝𝑛 1 + 𝜋𝑡𝑛
𝑃𝑁,𝑡
𝑃𝑁𝑖,𝑡
{
− 1}
+ 𝑀𝐶𝑡 𝜃 ()
𝑛𝑛
1 + 𝜋𝑠𝑠 1 + 𝜋𝑠𝑠
𝑃𝑁𝑖,𝑡−1
𝑃𝑁,𝑡

+𝛽

−𝜃−1

𝑛
𝛬𝑡+1 𝜂𝑝𝑛 1 + 𝜋𝑡+1
𝑃𝑁𝑖,𝑡+1 𝑌𝑁,𝑡+1{− 1} 2
𝑃 = 0.
𝑛𝑛
𝛬𝑡 1 + 𝜋𝑠𝑠 1 + 𝜋𝑠𝑠
𝑃𝑁𝑖,𝑡 𝑌𝑁,𝑡 𝑁,𝑡where 𝑀𝐶𝑡 denotes the marginal cost. Assuming that the symmetric equilibrium ex post further yields
𝑊𝑡
𝑃𝑁,𝑡

(22)

𝑀𝐶𝑡 𝐴𝑁𝑇𝑡 =(23)

𝑌𝑁,𝑡 = 𝐴𝑁𝑇𝑡 𝐿𝑁,𝑡(24)(1 − 𝜃) −𝑛
𝜂𝑝𝑛 1 + 𝜋𝑡𝑛
𝑃𝑁,𝑡𝛬𝑡+1 𝜂𝑝𝑛 1 + 𝜋𝑡+1
𝑃𝑁,𝑡+1 𝑌𝑁,𝑡+1
{
{
−
1}
+
𝑀𝐶
𝜃
+
𝛽
− 1}
=0
𝑡
𝑛
𝑛
𝑛
𝑛
1 + 𝜋𝑠𝑠 1 + 𝜋𝑠𝑠
𝑃𝑁,𝑡−1
𝛬𝑡 1 + 𝜋𝑠𝑠 1 + 𝜋𝑠𝑠
𝑃𝑁,𝑡 𝑌𝑁,𝑡where an equation (24) represents the New Keynesian Phillips curve.

13

3-4: Central Bank
Many previous studies have used an exchange rate-adjusted Taylor rule to account for imported foreign currencybased inputs, incomplete exchange rate pass-through, and external competitiveness in small open economies. In particular,
Froyen and Guender (2018) argue that after the global financial crisis in 2008-2009, exchange rate stability became a morecommon concern for emerging market central banks because of their expanded exposure to foreign investors in an
extremely low-interest-rate environment and their vulnerability to sudden stops. Moreover, in practice, as Guzman et al.
(2018) show, some central banks pursue real exchange rate stability, while others adjust the policy rate in response tonominal exchange rate fluctuations so that the nominal exchange rate is moderately fixed. In this context, we adopt the
Taylor rule, which considers not only traditional variables but also nominal exchange rate stability as follows:( 1 + 𝑖𝑡 )1 + 𝑖𝑡−1 𝜅𝑖 𝑃𝑡 𝜅𝑝 𝑌𝑡 𝜅𝑌 𝑆𝑡 𝜅𝑠=() () ( ) (
) exp (𝜖𝑡𝑖 )(1 + 𝑖𝑠𝑠 )1 + 𝑖𝑠𝑠
𝑃𝑡−1
𝑌𝑠𝑠
𝑆𝑡−1

(25)

where 𝑆𝑡 denotes the nominal exchange rate, and 𝜅𝑖, 𝜅𝑝, 𝜅𝑌, and 𝜅𝑠 denote the parameters of the nominal interest rate in
the t-1 period, CPI, GDP gap, and nominal exchange rate. These parameters determine how aggressively the central bankreacts to deviations in each variable from either the steady-state level or the level in the previous period.

3-5: Resource constraints and balance of payments
The following resource constraints hold for tradable and non-tradable goods sectors:(26)

𝑌𝑇,𝑡 = 𝐶𝐻,𝑡 + 𝐼𝐻,𝑡 + 𝑋𝑡

(27)

𝑌𝑁,𝑡 = 𝐶𝑁,𝑡(28)

𝑌𝑡 = 𝑌𝑇,𝑡 + 𝑃𝑁,𝑡 𝑌𝑁,𝑡 .

In addition, the labor market is balanced by(29)

𝐿𝑡 = 𝐿𝑁,𝑡 + 𝐿 𝑇,𝑡 .
Furthermore, assuming 𝑥𝑡+1 = 𝑥𝑡 = 1 , we obtain the following balance of payments (dynamic bond-holding

equation):

14

2

𝜂 It
𝑆𝑡 𝐵𝑡+1
𝜑 𝐵𝑡+1
𝑃𝐶𝐹,𝑡 𝐶𝐹,𝑡 + 𝑃𝐼𝐹,𝑡 𝐼𝐹,𝑡 + 𝑃𝐼,𝑡 ( − δ)2 Kt − 𝑋𝑡 =− 𝑆𝑡 𝑃𝐹,𝑡 (− 𝐵̅) − 𝑆𝑡 𝐵𝑡 + 𝑆𝑡 𝑃𝐶𝐹,𝑡 (𝛯𝑡𝑐 + 𝛯𝑡𝑑 )
(
)
2 Kt
1+𝑟
2 𝑃𝐹,𝑡+1
Here, the current account balance is defined as(30)

𝐶𝐴𝑡 ≡ 𝑋𝑡 − 𝑃𝐼𝐹,𝑡 𝐼𝐹,𝑡 − 𝑃𝐶𝐹,𝑡 𝐶𝐹,𝑡 − 𝑟𝑆𝑡 𝐵𝑡 + 𝑆𝑡 (𝛯𝑡𝑐 + 𝛯𝑡𝑑 )After aggregation, the remittance𝛯𝑡 is formulated as follows:(31)𝛯𝑡 = (𝛯𝑡𝑐 + 𝛯𝑡𝑑 ) + 𝛯𝑡𝑖𝑠

where

(32)

(33)

(34)

1−𝜌𝑅

𝑐
𝛯𝑡𝑐 = 𝛯𝑠𝑠𝛯𝑡𝑑 = (

𝜌

𝑐 𝑅
𝛯𝑡−1
𝑒𝑥𝑝 (𝜀𝑡𝑅 )𝑊𝑡 𝜂) 𝑟 , 𝑤ℎ𝑒𝑟𝑒 𝜂_𝑟 < 0𝑃𝑡𝛯𝑡𝑖𝑠 = 𝜇𝐼𝐹,𝑇 .

𝛯𝑡𝑐 is exogenously given and follows a stochastic AR (1) process. 𝛯𝑡𝑑 reflects the countercyclical nature of remittances andis inversely related to the real wage in the home country (Mandelman, 2013). 𝜂𝑟 denotes the real wage elasticity. 𝛯𝑡𝑖𝑠
captures the procyclical nature of remittances that characterizes private capital inflows, such as a type of remittances forthe purpose of investing in the home economy. In this formulation, 𝛯𝑡𝑖𝑠 finances a portion of the imported capital goods
𝐼𝐹,𝑇 .
Exports (= 𝑋𝑡 ) are exogenously determined by adopting the formulation of Gertler et al. (2007), as follows:

(35)

𝜉

𝑋𝑡 = 𝑒𝑡 𝑌𝑡𝐹

𝑌𝑡𝐹 is the output of the trading partner country (exogenous), 𝑒𝑡 denotes the real exchange rate, and 𝜉(> 0) is the elasticityof the real exchange rate with regard to exports. The real exchange rate is defined as:

(36)

𝑒𝑡 =

∗
𝑆𝑡 𝑃𝐹,𝑡𝑃𝑡∗
where 𝑃𝐹,𝑡is the foreign consumer price index in foreign currency units, and is taken as given.

15

3-6: Exogenous shocks
A series of exogenous shocks follow the AR(1) process as follows:

𝜌

1−𝜌

𝜌

1−ρ

ρ

𝐴
𝐴𝑇𝑡 = 𝐴𝑠𝑠 𝐴 𝐴𝑡−1
exp(𝜀𝑡𝑇 )

(38)

𝑁𝑇
𝑁𝑇
𝐴𝑁𝑇
𝐴𝑡−1
exp (𝜀𝑡𝑁𝑇 )𝑡 = 𝐴𝑠𝑠(39)

𝑖𝑛𝑣
PIF,t = 𝑃𝐼𝐹,ss𝑖𝑛𝑣 𝑃𝐼𝐹,t−1
exp(ε𝐼𝐹
t ).

1−𝜌𝑖

(40)

4.

1−𝜌

(37)

𝑖
𝜖𝑡𝑖 = 𝜖𝑠𝑠

𝜌

𝑖 𝑖
𝜖𝑡−1
exp (𝜀𝑡𝑖 )Bayesian estimation
4-1: Fixed parameters and steady states
Some parameter values were fixed and chosen based on the previous literature. The Frisch elasticity is fixed at

1.455, following Mendoza (1991), while the labor disutility parameter is set to 1 (Larey, 2015). The external debt parameter
determining the steady-state level of external debt is fixed at 13 to match the Philippines’ data, which is 28 percent of
nominal GDP as of 2023. The foreign nominal interest rate is given by 0.04 and does not change over time in the context
of small open economies. We fix the conventional values of 0.33 and 0.03 to the capital share and depreciation rate,
respectively. Following Acosta et al. (2009), the share of non-tradable goods in the consumption basket, 𝛾𝑐 , the share ofhome tradables in the tradable consumption basket, 𝛾ℎ , the share of home investment goods in the investment composite;
𝛾𝑖 , the share of investment goods imported abroad in the foreign tradable composite, 𝛾𝐹 , and each of these elasticities, 𝜌𝑐 ,𝜌ℎ , 𝜌𝑖 , 𝜌𝐹 are set at 0.55, 0.4, 0.5, 0.7, 0.4, 0.7, 0.2, and 0.1, respectively. We follow Uribe and Schmitt-Grohe (2017) andassign values of 2.0 for the intertemporal elasticity of substitution 𝜎 and 0.00742 for the portfolio adjustment cost 𝜑 .
Regarding the price elasticity of demand for the intermediate good 𝜃, we assign a value of 6 such that a markup becomes
1.2, while the price adjustment cost parameter, 𝜂𝑝𝑛 , is set at 58.252, so the share of reoptimizing firms is 0.25 under the
given mark-up as in Keen and Wang (2007). We set the steady-state remittance to GDP at about 10%, while the share of
non-tradable labor at the steady state is set at 0.67, consistent with Philippine data.
Table.1 Fixed parameters

Parameter
i

Value
0.04

Description
Nominal interest rate on foreign bonds

16

𝛿
𝛼
𝜏
𝜈
𝜎
𝐵̅
𝜑𝐵
𝜌𝑐
𝜃
𝜂𝑝𝑛
𝜌ℎ
𝜌𝑖
𝜌𝐹
𝛾𝑐
𝛾ℎ
𝛾𝑖
𝛾𝐹
𝜂
𝐵𝐹,𝑠𝑠
𝑌𝑠𝑠
𝑅𝑠𝑠
𝑌𝑠𝑠
𝐿𝑁,𝑠𝑠
𝐿𝑠𝑠

0.03
0.33
1.0
1.455
2.0
13
0.00074
0.4
6.0
58.252
0.7
0.2
0.1
0.55
0.40
0.50
0.7
2.2
0.28
0.10
0.67

Capital Depreciation rate
Capital Share
Disutility parameter of Labor
The Frisch elasticity
the intertemporal elasticity of substitution of consumption
Parameter determining the external debt level of steady state
Portfolio adjustment cost
Elasticity of substitution between non-tradable to tradable consumption goods
the price elasticity of demand for the intermediate good
Price adjustment cost
Elasticity of foreign traded consumer goods/domestically traded consumer goods
Elasticity of foreign investment goods / domestic investment goods
Elasticity of foreign tradable goods/ elasticity of foreign imported materials
the share of non-tradable goods in the consumption basket
the share of home tradables in the tradable consumption basket
the share of home investment goods in the investment composite
the share of investment goods imported abroad in the foreign tradable composite
Adjustment cost parameter for investment
Steady state level of external debt
Steady state level of remittance to GDP
Steady state level of non-tradable labor to Aggregate labor
Created by Author

4-2: Estimation methodology, data, and results
We estimate the above model using data from the Philippines to investigate whether remittances induce Dutch
disease. To align the data with the model, the Bayesian estimation technique is applied to some of the parameterscharacterizing the Philippines’ exchange regime.
Data

We use five series of quarterly data from the Philippines: remittances, interest rate on the government

treausry bill, nominal exchange rate (Philippines peso to USD), tradable output1, and consumer price index, ranging from
1989Q1 to 2023Q3, and all the data are seasonally adjusted. Because the model variables represent deviations from thesteady state, we linke the model variables to the data as follows:

𝑅𝑡
)
𝑅̅
𝑆𝑡
𝑆̂𝑡 = 𝐿𝑜𝑔( )𝑆̅𝐼𝑡1𝑖̂𝑡 = 𝐿𝑜𝑔 ( ) ∗ ( )̅𝐼4𝛯̂𝑡 𝑡 = 𝐿𝑜𝑔(

1 Tradable output includes value added of manufacturing and mining sectors.

17

𝑃𝑡𝑃̂𝑡 = 𝐿𝑜𝑔( )𝑃̅𝑌𝑇,𝑡𝑌̂𝑇,𝑡 = 𝐿𝑜𝑔( )̅̅̅𝑌𝑇where the left-hand side of the equations denotes the model variables and the right-hand side equations represent the data.
The variables with bars are detrended with Hodrick and Prescott filters, and here represent the steady states.
Priors Paratmeters characterizing the Taylor rule and those that are data-dependent, with few past studies, areconsidered to be estimated. These include 𝜅𝑖, 𝜅𝑝, 𝜅𝑌, 𝜅𝑠, 𝜆, 𝜂𝑟 , 𝜉, 𝜌𝐴𝑇 , 𝜌𝑁𝑇 , 𝜌𝑅 , 𝜌𝑖 , 𝜌𝑧 , and the standard deviations of theremittance shock 𝜎𝑅 , tradable productivity shock 𝜎𝐴𝑇 , non-tradable productivity shock 𝜎𝑁𝑇 , terms of trade shock 𝜎𝑖 , andmonetary policy shock 𝜎𝑧 . We choose a proir mean of -0.5 for the remittance elasticity with a normal distribution to capture
the countercapacitality of remittances, as in Mandelman (2013). The prior means of interest coefficient, 𝜅𝑖 , inflation
coefficient, 𝜅𝑝, and GDP gap coefficient, 𝜅𝑌, are set at 0.3, 2.0, and 1.0, respectively. For the nominal exchange rate (NER)
coefficient 𝜅𝑠, we assign a mean of 1.0, so that the central bank is assumed to pay closer attention to nominal exchange
rate fluctuations. Regarding the share of hand-to-mouth households, we set 0.45, given the estimated posterior means ofMandelman (2013), while export elasticity was set relatively high at 2.0.
Tabel 2： Summary statistics for the prior and posterior distribution of the parameters

PriorsDescription

Posteriors

Name

DensityMean

Std Dev

GHH Median

CRRA MedianInterest Coeff in TR

𝜅𝑖

Gamma

0.3

0.1

0.03940.0364

Inflation Coeff in TR

𝜅𝑝

Gamma

2.2

0.25

3.02762.4988GDP gap Coeff in TR

𝜅𝑌

Gamma

1.0

0.25

0..1618

0.1315NER Coeff in TR

𝜅𝑠

Gamma

1.0

0.2

0.74140.4375Hand-to-mouth household share

𝜆

Gamma

0.45

0.2

0.47930.8773Remittance elasticity

𝜂𝑟Normal-0.5

0.1-0.1809-0.9422

Export Elasticity

𝜉

Gamma

2.0

0.2

3.14593.3030Tradable productivity shock

𝜌𝐴𝑇

Beta

0.5

0.1

0.48090.46

Non-tradable shock

𝜌𝑁𝑇

Beta

0.5

0.1

0.48320.7188Remittance shock

𝜌𝑅

Beta

0.5

0.1

0.48280.5385

Terms of trade shock

𝜌𝑖

Beta

0.5

0.1

0.9386

0.3914

Monetary policy shock

𝜌𝑧

Beta

0.5

0.1

0.0631

0.0412Remittance shock sd

𝜎𝑅

Inv gamma

0.5

Inf

0.06010.080118

Tradable shock sd

𝜎𝐴𝑇

Inv gamma

0.5

Inf

0.06770.0605

Non-tradable shock sd

𝜎𝑁𝑇

Inv gamma

0.5

Inf

0.06050.0602

Terms of trade shock sd

𝜎𝑖

Inv gamma

0.5

Inf

0.14980.1129

Monetary shock sd

𝜎𝑧

Inv gamma

0.5

Inf

0.15530.1586

Estimation Resuts (Posteriors)

The last two columns of Table 2 show the summary statistics of the posteriorsof the parameters. Among the estimated means, the NER coefficient in the Taylor rule is found to be significantly lower
than the infaltion coeffeicient in both GHH and CRRA preferences, suggesting that the central bank of Philippines adopts
free floating exchange rate regime, consistent with the IMF's de facto classification of the Philippines as a "floating regime,.”Regarding the remittance elasticity of real wages, the estimated median values remain in the negative range, confirming
the countercyclical nature of remittances, although the estimated value is lower in the GHH specification than in CRRA.
The share of hand-to-mouth households in GHH preferences is estimated at 0.4793, which is very close to the result ofMandelman (2013). However, for the CRRA preference, the share of the hand-to-mouth household is estimated at 0.8773,
which is significantly higher than the GHH, which might reflect the larger role of self-insurance households in the presenceof income effects from remittances.

4-3: An analysis from Bayesian IRFs
4-3-1: the role of the income effectFigure 3 shows the impulse response functions using the median values of the posterior distributions of theBayesian estimated parameters for a one-standard-deviation remittance shock. The black line represents the response ofeach variable under a GHH utility function with no income effect, whereas the blue line represents the response under a
CRRA utility function that includes the income effect.
In both utility functions, an increase in remittances relaxes the household budget constraint, leading to an increasein consumption and appreciation of the nominal exchange rate (a decrease in St). In both cases, the parameter for thenominal exchange rate in the Taylor rule is significantly lower than that of inflation, allowing the exchange rate to move
relatively freely. The increase in consumption leads to an expansion of the non-tradable sector and increases prices.
However, in the case of the GHH utility function, consumption gradually begins to decline, leading to a decrease in demandand subsequent decrease in prices in the non-tradable goods sector. This occurs because under the GHH utility function
with no income effect, Ricardian households increase both consumption and labor supply simultaneously, leading to adecrease in real wages. Consequently, the labor supply of hand-to-mouth households decreases, making it unsustainable

19

for them to maintain their consumption levels.
By contrast, under the CRRA utility function with an income effect, while Ricardian households increase
consumption, they simultaneously reduce their labor supply due to the income effect, leading to an increase in real wages.
This causes hand-to-mouth households to increase their labor supply, thereby sustaining their consumption. As a result,overall consumption under the CRRA utility function continues to increase in the medium to long term.
The real exchange rate appreciates in response to an increase in remittances under both the utility functions. Unlike
Acosta et al. (2009), who do not consider nominal exchange rate fluctuations, the real exchange rate is determined by the
movements of domestic prices and the nominal exchange rate. Regardless of the utility function, the impact of the nominal
exchange rate on the real exchange rate is greater than that of domestic prices, making the real exchange rate primarily
driven by nominal exchange rate movements. The appreciation of the real exchange rate reduces exports, leading to adecrease in the tradable sector output. On the other hand, the increase in consumption demand due to remittances isabsorbed by the non-tradable sector, causing the reallocation of resources from the tradable sector to the non-tradable sector,
resulting in Dutch disease regardless of the presence of an income effect. However, the impact of the resource reallocation
effect is greater under the CRRA utility function with an income effect even though the appreciation of the real exchange
rate is relatively moderate. This is primarily due to the difference in the magnitude of the labor supply to the tradable sector.
As mentioned earlier, under the CRRA utility function with an income effect, the overall reduction in labor supply is greaterthan that under the GHH utility function; as a result, the reduction in labor supply to the tradable goods sector is also greater,
leading to a more significant decline in the tradable sector. The difference in labor supply is consistent with the results of
Acosta et al. (2009), but in contrast to their study, where tradable output slightly increases in the absence of income effects(GHH preference), in this model with a central bank, the increase in prices due to the increase in remittances leads to anincrease in interest rates by the central bank, reducing investment and capital, which in turn prevents an increase inproduction in the tradable goods sector, even under the GHH utility function.
Figure 3：Bayesian Impulse response functions to the remittance shock20

Source: Created by the author. The solid blue line denotes CRRA preferences. The black solid line indicates the baseline GHH
preferences. The dashed line represents the 90% credit interval.

4-3-2: The role of exchange rate regime
As a counterfactual scenario, we intentionally set a high value for the nominal exchange rate parameter of the
Taylor rule, assuming a central bank prefers to avoid exchange rate fluctuations over inflation. Here, we examine thedifferences in exchange rate regimes under the GHH utility function, without an income effect. All other parameters are
the same as those estimated using the Bayesian methods in Section 4. Figure 4 shows the differences in impulse response
functions following a one-standard-deviation remittance shock. The solid blue line represents the benchmark model using
the estimated parameters, whereas the dashed blue line represents the counterfactual model in which the central bank adopts
a fixed exchange rate regime aimed at minimizing exchange rate fluctuations.
First, in both models, a remittance shock leads to an increase in consumption; however, the consumption response
is larger under the fixed exchange rate regime partly due to interest rate cuts. Under the floating exchange rate regime (theestimated benchmark model), the central bank responds to the inflationary pressures arising from the remittance shock by21

raising interest rates, whereas in the fixed exchange rate regime, the central bank lowers interest rates to counteract theappreciation of the exchange rate caused by the remittance inflows. In the latter case (fixed exchange rate regime), because
the model uses a GHH utility function with no income effect, the overall labor supply increases significantly, leading to a
substantial decrease in nominal wages. Consequently, the marginal cost for firms in the non-tradable-goods sector decreases,
resulting in a decline in non-tradable prices in response to the remittance shock2.
The combined impact of the decline in prices and a slight depreciation of the nominal exchange rate caused by
the rate cuts under the fixed exchange rate regime leads to a depreciation in the real exchange rate, enhancing pricecompetitiveness and resulting in an increase in exports. Furthermore, the reduction in interest rates accelerates investment,
leading to greater capital accumulation, which boosts production in the tradable sector. In this case, the remittance shockleads to an expansion in production in both tradable and non-tradable goods sectors, preventing the resource reallocation
effect that would otherwise cause a contraction in the tradable goods sector.
Figure 4：Bayesian Impulse response functions to the remittance shock

2 Although CPI inflation decreases at the time of the remittance shock due to a decline in wages, it sharply increases from the second

period onward as demand rises from the remittances, with the inflationary pressure continuing until eighth period.

22Source: Created by the author. The blue solid line represents the baseline-estimated GHH model. The dashed line represents the fixedexchange rate regime, with the value of parameter 𝜅𝑠 set arbitrarily high.

4-3-3: Exchange rate regime and income effectFigure 5 illustrates the differences in the exchange rate regimes under CRRA preferences with the income effectin response to a remittance shock to compare the model dynamics depending on the presence of the income effect (GHHvs CRRA). The solid blue line represents the estimated benchmark model, where the parameter value for the exchange rate
fluctuations in the Taylor rule is estimated to be 0.4375, which is significantly lower than the parameter for pricefluctuations at 2.49, assuming a free-floating exchange rate regime, as in the GHH preference. The dashed blue line shows
the impulse response function under a fixed exchange rate regime, where the nominal exchange rate parameter isintentionally set high to drastically suppress the exchange rate fluctuations.
Under the fixed exchange rate regime, the remittance shock leads to a more significant increase in consumption
and labor, similar to the GHH model; however, the overall increase in labor supply is weaker compared to the GHH modeland eventually becomes negative in the medium to long term. While the rise in real wages provides households with an
incentive to increase their labor supply, the income effect from remittances partially offsets this, resulting in restraint onlabor supply. Similar to the GHH model, the central bank in the fixed exchange rate regime responds to the remittanceshock by lowering interest rates, causing depreciation of the nominal exchange rate. While strong consumption demand
increases non-tradable prices, the impact of nominal exchange rate depreciation is stronger, resulting in a slight depreciationin the real exchange rate. Although exports show an increasing response, tradable output declines, unlike in the GHH model.
The stimulation of investment and capital accumulation through interest rate cuts is similar to the GHH model; however,the constraint on labor supply plays a significant role. The overall labor supply by households is considerably lower thanthat in the GHH model, and this increase in labor supply is entirely absorbed by the expansion of the non-tradable sector.
As a result, unlike the GHH model, under the CRRA model, even when adopting a fixed exchange rate regime andsuppressing the effects of the exchange rate, the Dutch disease effect is exacerbated due to the reallocation of labor supply.
This finding complements the argument made by Acosta et al. (2009), who show that labor reallocation effects are crucial
for the Dutch disease effect. It also supports the research by Bayangos and Jansen (2011), which demonstrates that in thePhilippines, the contraction of the tradable sector is more strongly driven by labor shifts than by exchange rate effects. The
combined results from Figures 4 and 5 indicate that the presence of the income effect could overweigh the importance ofthe exchange rate regime, suggesting that the monetary easing effect in response to remittances and associated realexchange rate depreciation may not be sufficient to sustain the expansion of the tradable sector in the presence of the23

income effect.
Figure 5：Bayesian IRFs to the remittance shock-CRRA preferences and different exchange rate regimes

Source: Created by the author. The solid blue line represents the baseline estimated CRRA model. The dashed line represents the fixedexchange rate regime, with the value of parameter 𝜅𝑠 set arbitrarily high.

4-3-4: The effect of hand-to-mouth households
The above discussion shows that the tradable sector could potentially expand when the income effect ofremittances is absent, and the central bank stabilizes the exchange rate by lowering interest rates in response to a remittanceshock. Here, we examine the impact of remittances based on household heterogeneity under a fixed exchange rate regime.
The solid blue line represents the impulse response function of a two-household model, which includes hand-to-mouthhouseholds, whereas the dashed line represents the response of a model with only Ricardian households. When hand-tomouth households are present, the increase in remittances is used entirely for consumption in the current period, resulting
in a larger consumption response. Additionally, the rapid increase in labor supply leads to a sharp decline in wages, which
has a stronger effect on lowering prices. While CPI inflation initially declines in both models, strong demand surge in the24

presence of hand-to-mouth households in response to a remittance shock leads to a subsequent sharp rise in inflation.
The central bank implements a significant interest rate cut, resulting in more pronounced depreciation of thenominal exchange rate in the two-household model. As a result, the real exchange rate experiences stronger depreciation,
leading to a substantial expansion of the tradable sector to the remittance shock. However, the model's dynamics, in which
the remittance shock leads to an expansion of the tradable-goods sector, remain unaffected by household heterogeneity.
Figure 6：Bayesian IRFs to the remittance shock-GHH preferences and household heterogeneity

Source: Created by the author. The solid blue line represents the estimated two-agent GHH model. The dashed line shows therepresentative model with only Ricardian households.

4-3-5: The counter- and pro-cyclical remittances
Figure 7 and 8 show the impulse response functions to a one-standard-deviation decline shock in the productivityof the tradable sector and in the price of foreign investment goods, respectively. A shock to the productivity of the tradable
sector leads to a contraction in tradable output. Contraction in the tradable sector depresses real wages, leading to a decline
in the aggregate supply of labor. In the CRRA model, consumption increases slightly in response to a productivity decline25

shock. This reflects support for consumption from countercyclical remittance inflows, which counteract the decline in real
wages. On the other hand, in the GHH model, consumption falls sharply, as hand-to-mouth households sharply reduce theirspending in response to the productivity decline shock. In the CRRA model, a slight increase in consumption demand isabsorbed by the expansion of the non-tradable goods sector, exacerbating the Dutch disease effect.
A decline in the price of foreign investment goods leads to an increase in foreign investment goods. Since these
foreign investment goods are financed partially by procyclical remittances, similar to foreign investment, this shock can beseen as a shock of increased FDI-like remittance inflows. Irrespective of the presence or absence of the income effect, thefall in the price of investment goods first exerts downward pressure on domestic prices, leading to depreciation of the realexchange rate. Additionally, the expansion of domestic investment promotes capital accumulation, leading to an increasein output in the tradable goods sector. While domestic demand weakens, external demand strengthens owing to the
expansion of exports, causing domestic resources to shift to the tradable goods sector. Thus, by financing investment, FDIlike remittances do not lead to Dutch diseases.
Figure 7：Bayesian IRFs to the negative tradable productivity shock26

Figure 8：Bayesian IRFs to the negative foreign investment price shock

Source: Created by the author. The solid blue line denotes CRRA preferences. The black solid line indicates the baseline GHH
preferences. The dashed line represents the 90% credit interval.

5.

Discussion and an application in the case of Philippines
The previous estimation results indicate that the impact of increased remittances on the real exchange rate is

influenced not only by price differentials but also by fluctuations in the nominal exchange rate. In the Philippines, theexchange rate regime is classified as floating exchange rate regime according to the IMF's de facto classification, whichaligns with the low values of the parameter for exchange rate fluctuations in the Taylor rule. Historically, during the rapid
increase in remittances from the 2000s to the 2010s, the Philippines experienced a significant current account surplus andrapid accumulation of foreign reserves. According to the IMF (2007), the correlation between changes in foreign reservesand currency interventions (dollar purchases and peso sales) by the central bank is extremely high, ranging from 0.8 to 0.9,
suggesting that increase in foreign reserves is almost entirely done by the currency interventions. They also show that theseinterventions occur during periods of increasing local currency appreciation pressure. These historical facts are consistent27

with the results of the model, showing that an increase in remittances contributes to currency appreciation and that thePhilippine peso can move relatively freely.
Another important mechanism that the estimation results demonstrate is the presence of the income effect ofremittances, which leads to significant differences in the outcomes of the resource movement effect. As shown in the resultsof CRRA preference, the presence of the income effect could potentially offset the positive effects of the fixed exchange
rate regime such as promoting investment and prevention of the real exchanger rate appreciation. Regarding the income
effect, while it is known to vary by gender, region, and country (Posso, 2012; Azizi, 2018), empirical studies on thePhilippines have accumulated evidence suggesting that remittances reduce domestic labor supply. For instance, Cabegin(2013), using survey data from the Philippines, demonstrates that the working hours of households receiving remittances
decrease with an increase in remittances. This effect is particularly pronounced in households with children, where surplus
time created by remittances is spent on activities such as children's education, further reducing working hours. Similarly,
Rodriguez and Tiongson (2001) find a negative relationship between short-term overseas migration and the working hours
of relatives left behind in the Philippines. Yang (2008) points out that the depreciation of the peso during the Asian financial
crisis led to a sharp increase in remittances denominated in local currency. He takes this as an exogenous remittance shock
and finds that an unexpected increase in remittance flows leads to a decrease in child labor and an increase in educational
opportunities in the home country. On the other hand, in the case of self-employment, the remittance shock significantly
increases working hours, suggesting that in certain industries, remittances could lead to an increase in labor supply. Froma macroeconomic perspective, Vu (2023) shows through a VAR model that the remittance shock significantly reduces thelabor force participation rate in the Philippines, which also aligns with the empirical results of Bayangos and Jansen (2011).
In light of these empirical findings and stylized facts, it could be suggested that in the Philippines, in addition to
the effects of exchange rates under a floating exchange rate regime, the resource movement effects due to a decline in labor
supply are also significant, hindering the development of tradable sectors, as is the case with the estimation results of the
CRRA specification that includes an income effect.

6.

Conclusion
This study analyzes the Dutch disease effect of the recent surge in remittances using a DSGE model thatincorporates exchange rate regimes and explores the factors that strengthen Dutch disease. While a sharp increase inremittances can appreciate the real exchange rate of recipient countries and hinder the development of the tradable sector,
empirical results vary across regions and countries, leaving considerable room for debate on the factors that exacerbate thenegative effects of remittances. Given the wide range of exchange rate regimes in remittance-receiving countries and the28tendency for the real exchange rate to overshoot without adjusting through nominal exchange rates or prices, it is crucial
to consider the exchange rate regime when analyzing the Dutch disease effect of remittances. However, there is limited
research analyzing the Dutch disease effect of remittances caused by differences in exchange rate regimes. While somestudies analyze the relationship between remittances and exchange rate systems (Lartey (2015), Ball, et al (2012) and
Mandelman (2013)), these studies abstract important characteristics of remittances, such as household heterogeneity,
countercyclical nature, resource movement effects, and income effects. To fill these gaps, this study extends the models of
Acosta et al. (2009) and Mandelman (2013) by constructing a two-household two-sector DSGE model that incorporates
exchange rate regimes.
The main findings are as follows: First, contrary to the findings of Acosta et al. (2009), who show that theremittance shock leads to a slight expansion of tradable output in the absence of income effects, this study shows that when
the central bank adopts a floating exchange rate regime, the increase in interest rates caused by remittances inhibits
investment, thereby preventing the expansion of the tradable sector, even when there are no income effects of remittances.
This study also finds that the tradable sector can expand under a fixed exchange regime in the absence of income effects
from remittances because rate cuts lead to currency depreciation and promote investment. However, when there is an
income effect, its effect on a decline in labor supply to the tradable sector offsets the positive effects of rate cuts, leading
to a contraction of tradable output and Dutch disease through resource movement effects. These results suggest thatdifferent exchange rate regimes alone may not prevent resource movement effects and that the income effect of remittances
may be a key determinant in the dynamics of Dutch disease. This finding supports the results of Acosta et al. (2009) and
Mandelman (2013), who argue that the presence or absence of income effects is crucial to the Dutch disease effect ofremittances.
In the case of the Philippines, the estimated value of the exchange rate parameter in the Taylor rule is significantly
lower than the parameter for price stability, suggesting that the country adopts a floating exchange rate regime, consistent
with the IMF's de facto classification. Given the empirical findings of Vu (2023) and micro-level empirical evidence
showing that remittances reduce the labor supply of households in the home country, there is a possibility, as suggested by
the CRRA-type estimation results of this study, that remittances in the Philippines amplify the Dutch disease through bothexchange rate and income effect channels.
However, this study fails to fully analyze the endogenous dynamics of migration and does not account for theeffects of migration from the home country to other countries. Future research could analyze the differences in exchange
rate regimes within a two-country model framework.

29

7.

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32

8.

Appendix
Priors/Posterior Distributions and Convergence Diagnostics
The prior and posterior distributions of the parameters for GHH and CRRA preferences are shown in Figure 9 and

10 respectively. To estimate the parameters, Markov chain Monte Carlo (MCMC) sampling is performed based on the
Metropolis (MH) algorithm. The scale parameters are determined so that the acceptance rate would fall within 25-35%,
and 200,000 sampling runs are conducted. The first 100,000 are rejected as burn-in and the remaining 100,000 are accepted.
Figure 11 shows the change in statistics by Brooks and Gelman (1998), which confirms that the two Markov chainsconverge to constant values for both moments.
Figure 9: Prior and Posterior distributions of the parameters - GHH preferences

Figure 10: Prior and Posterior distributions of the parameters – CRRA preferences

Figure 11: Convergence Diagnostics based on Brooks and Gelman (1998) statistics

33

GHH preferences (LHS) and CRRA preferences (RHS)

34