Religion and cooperative attitudes: Evidence from
Abstract: Using the latest round of the Indonesian Family Life Survey (IFLS),
I investigate the correlations between religion and cooperative attitudes
such as altruism, trust, and tolerance. I investigate these associations
for dierent religions in Indonesia, a country where Islam is the majority religion but recognizes other world religions such as Catholicism,
Protestantism, Hinduism, Buddhism, as well as Confucianism. Meanwhile, the attitudes studied here naturally fall under what Guiso et al.
(2011) called "civic capital", i.e., "those persistent and shared beliefs
and values that help a group overcome the free rider problem in the
pursuit of socially valuable activities".
I find that: (i) religiosity is associated with a higher willingness
to help and trust of individuals within one's own community, but not
with the (generalized) trust of strangers; (ii) however, religiosity is
associated with more religious discrimination; (iii) interestingly, but
consistent with the social psychology literature, religiosity is also as-
sociated with greater ethnic discrimination; and (iv) among Muslims
and, to a much lesser extent, Protestants, religiosity is negatively associated with tolerance. The evidence, therefore, suggests that religion
may be linked to "parochial altruism" (Bernhard et al., 2006; Choi and
Bowles, 2007), which is altruism towards members of one's own group
combined with hostility towards members of the out-groups. The link
appears to be strongest for adherents of the country's majority religion.
Keywords: religion, cooperation, parochial altruism, Indonesia
JEL Classifications: D71, D72, Z12
On Identification of Bayesian DSGE Models
Gary Koop, M. Hashem Pesaran, Ron P. Smith
Abstract: In recent years there has been increasing concern about the identifi-
cation of parameters in dynamic stochastic general equilibrium (DSGE)
models. Given the structure of DSGE models it may be difficult to determine whether a parameter is identified. For the researcher using Bayesian
methods, a lack of identification may not be evident since the posterior
of a parameter of interest may differ from its prior even if the parameter
is unidentified. We show that this can even be the case even if the priors
assumed on the structural parameters are independent. We suggest two
Bayesian identification indicators that do not suffer from this difficulty and
are relatively easy to compute. The first applies to DSGE models where
the parameters can be partitioned into those that are known to be identified and the rest where it is not known whether they are identified. In such
cases the marginal posterior of an unidentiÖed parameter will equal the
posterior expectation of the prior for that parameter conditional on the
identified parameters. The second indicator is more generally applicable
and considers the rate at which the posterior precision gets updated as
the sample size (T) is increased. For identified parameters the posterior
precision rises with T, whilst for an unidentified parameter its posterior
precision may be updated but its rate of update will be slower than T.
This result assumes that the identified parameters are pT-consistent, but
similar di§erential rates of updates for identified and unidentified parameters can be established in the case of super consistent estimators. These
results are illustrated by means of simple DSGE models.
JEL Classifications: C11, C15, E17
Keywords: Bayesian identification, DSGE models, posterior updating, New Keynesian Phillips Curve.
Aggregation in Large Dynamic Panels
M. Hashem Pesaran, Alexander Chudik
Abstract: This paper considers the problem of aggregation in the case of large linear dynamic panels,
where each micro unit is potentially related to all other micro units, and where micro innovations
are allowed to be cross sectionally dependent. Following Pesaran (2003), an optimal aggregate
function is derived, and the limiting behavior of the aggregation error is investigated as N (the
number of cross section units) increases. Certain distributional features of micro parameters
are also identified from the aggregate function. The paper then establishes Granger's (1980)
conjecture regarding the long memory properties of aggregate variables from 'a very large scale
dynamic, econometric model', and considers the time profiles of the effects of macro and micro
shocks on the aggregate and disaggregate variables. Some of these findings are illustrated
in Monte Carlo experiments, where we also study the estimation of the aggregate effects of
micro and macro shocks. The paper concludes with an empirical application to consumer price
inflation in Germany, France and Italy, and re-examines the extent to which 'observed' inflation
persistence at the aggregate level is due to aggregation and/or common unobserved factors. Our findings suggest that dynamic heterogeneity as well as persistent common factors are needed for
explaining the observed persistence of the aggregate inflation.
Keywords: Aggregation, Large Dynamic Panels, Long Memory, Weak and Strong Cross Section
Dependence, VAR Models, Impulse Responses, Factor Models, Inflation Persistence.
JEL Classification: C43, E31
Auctions with Resale and Bargaining Power
Abstract: We show that when the weak bidders bargaining power in the resale market is weakened, the auc
tioneers revenue from the first-price auction with resale is lower. Using the idea of Coase Theorem, we
show that when the resale market is a sequential bargaining model with no commitment, the auctioneers
revenue is substantially reduced, and the ranking is the opposite of Hafalir and Krishna (2009). We establish a version of the Coase Theorem in the context of the auctions with resale. When Coase Theorem
holds, we show that the revenue of the auction with resale is lower than the revenue of the same auction
without resale. We also provide the existence and uniqueness of equilibrium for our model of auctions
Keywords: Resale, Existence and uniqueness of equilibrium, Bargaining Power, Auction revenue,
JEL Classification: D4, D8, L1
Midwives and Maternal Mortality: How Effective has Indonesia's Village Midwife Program Been?
Shailender Swaminathan, Tomoya Matsumoto, and Jeffrey B. Nugent
Objective: To assess the effect of Indonesia’s Village Midwife Program on Maternal Mortality Rates
Methods: Use data from the Demographic and Health Surveys (years) to construct a time series (1985-2002) of estimates of Maternal Mortality Rates-separately for rural and urban areas- using the Sisterhood method. Use data from the Indonesian Family Life Survey (years) to construct estimates of village midwife availability, and also a time series of both the Crude Birth Rate and the Teenage Birth Rates-separately for rural versus urban areas. Use regression analysis to identify the effect of village midwives after controlling for other correlates such as maternal education, and maternal age at pregnancy.
Findings: Between the time in 1993 when the deployment of midwives began in earnest and 2000, the majority of the trained midwives were deployed to rural areas, and resulted in a large reduction in the rural-urban gap in MMRates over this period. We also find a reduction in the rural-urban difference in Crude Birth Rates and Teenage Birth Rates. Together these results suggest that village midwives may have impacted maternal mortality rates by improving access to family planning methods, and by reducing unsafe abortion practices. The results are robust to the consideration of other factors such as changes in mother characteristics and access to other sources of maternal care.
Key Words: maternal mortality, Indonesia, village midwife
Off-farm labor supply and labor markets in rapidly changing
circumstances: Bulgaria during transition
Sumon Kumar Bhaumik, Ralitza Dimova, Jeffrey B. Nugent
Abstract: This study examines off-farm labor supply in the rapidly changing
conditions of Bulgaria during the 1990s. In doing so, we make use of
three different waves of the Bulgarian Integrated Household Survey,
each reflecting remarkably different environmental conditions. The
results suggest that standard theories of off-farm labor supply
provide little guidance in situations characterized by chronic excess
supply in the off-farm labor market and/or rapidly changing
circumstances. In particular, the results show (1) that off-farm employment throughout the transition was predominantly determined
by demand rather than by supply, and (2) that the magnitude
and statistical significance of the various determinants are very
sensitive to changing environmental conditions. As such, the results
can be extremely relevant for both theory and policy for the many
countries which may still need to go through privatization and
painful restructuring as a result of financial crises and globalization.
Keywords: Off-farm labor supply,
JEL Classification: J2,
Lobbying or Information Provision-Which Functions of Associations Matter Most for
Grigor Sukiassyan, Jeffrey nugent
Abstract: Private firms are of growing importance in virtually all transition
economies but operate in market and institutional conditions that are still
far from competitive and transparent. Although firms have at their disposal
various alternative strategies for dealing with their problems, in this paper
we focus on two: making unofficial payments to officials and joining business
associations. Choices between these strategies may be affected by both
firm and industry characteristics and institutional conditions. This paper
has two objectives: (1) to compare the effects of two alternative strategies
(unofficial payments and association memberships) on various alternative
measures of firm performance; and (2) in the case of association membership,
to determine which particular functions—lobbying, information, or other— have the greatest effects on several different measures of firm performance.
To accomplish these objectives, we make use of the 2002 and 2005 waves of
the Business Environment and Enterprise Performance Surveys in twentyeight
transition economies. Estimates are obtained from both separate cross
sections for 2002 and 2005 and a smaller panel of firms for which the information
is available for both years. The estimates show that memberships in
business associations, and especially access to their information functions,
contribute more to firm performance than unofficial payments and lobbying,
despite the fact that much of the literature asserts the opposite and assumes
lobbying to be the primary function of business associations, especially in
Is there an optimal forecast combination?
Cheng Hsiao, Shui Ki Wan
Abstract: We consider several geometric approaches for combining forecasts in large samples a simple
eigenvector approach, a mean corrected eigenvector and trimmed eigenvector approach. We give
conditions where geometric approach yields identical result as the regression approach. We also
consider a mean and a mean and scale corrected simple average of all predictive models for finite
sample and give conditions where simple average is an optimal combination. Monte Carlos
are conducted to compare the finite sample performance of these and some popular forecast
combination and information combination methods and to shed light on the issues of "forecast
combination" vs "information combination". We also try to shed light on whether there exists
an optimal forecast combination method by comparing various forecast combination methods
to predict US real output growth rate and excess equity premium.
Measurement Errors and Censored Structural Latent Variables
Songnian Chen, Cheng Hsiao, Liqun Wang
Abstract: We consider censored structural latent variables models where some exogenous variables
are subject to additive measurement errors. We demonstrate that overidentification conditions
can be exploited to provide natural instruments for the variables measured with errors and
we propose a two stage estimation procedure. The first stage involves substituting available instruments in lieu of the variables that are measured with errors and estimating the resulting
reduced form parameters using consistent censored regression methods. The second stage
obtains structural form parameters using the conventional linear simultaneous equation model
Keywords: Censored responses; errors-in-variables; instrumental variables; latent variables; limited
dependent variables; simultaneous equations; Tobit model.
JEL Classification: C13; C34.
Measuring correlations of integrated but not
cointegrated variables: a Semiparametric
Yiguo Sun, Cheng Hsiao, Qi Li
Abstract: Many macroeconomic and financial variables are integrated of order one (or I(1))
processes and are correlated with each other but not necessarily cointegrated. In this
paper, we propose to use a semiparametric varying coefficient approach to model/capture
such correlations. We propose two consistent estimators to study the dependence relationship
among some integrated but not cointegrate time series variables. Simulations
are used to examine the finite sample performances of the proposed estimators.
Keywords: Integrated time series; Non-cointegration; Semiparametric varying coefficient models.
JEL Classification: C13, C14, C20
Method of Moments Estimation and Identifiability of
Semiparametric Nonlinear Errors-in-Variables Models
Liqun Wang, Cheng Hsiao
Abstract: This paper deals with a nonlinear errors-in-variables model where the distributions of the
unobserved predictor variables and of the measurement errors are nonparametric. Using the
instrumental variable approach, we propose method of moments estimators for the unknown
parameters and simulation-based estimators to overcome the possible computational difficulty
of minimizing an objective function which involves multiple integrals. Both estimators are consistent
and asymptotically normally distributed under fairly general regularity conditions. Moreover,
root-n consistent semiparametric estimators and a rank condition for model identifiability
are derived using the combined methods of nonparametric technique and Fourier deconvolution.
Keywords: Fourier deconvolution, identifiability, instrumental variables, measurement error,
method of moments, root-n consistency, semiparametric estimator, simulation-based estimator.
JEL Classification: C13, C14, C15.
China's Emergence in the World Economy and Business Cycles in Latin America
Ambrogio Cesa-Bianchi, M. Hashem Pesaran, Alessandro Rebucci, TengTeng Xu
Abstract: The international business cycle is very important for Latin America's economic performance as the recent global crisis vividly illustrated. This paper investigates how changes
in trade linkages between China, Latin America, and the rest of the world have altered the
transmission mechanism of international business cycles to Latin America. Evidence based
on a Global Vector Autoregressive (GVAR) model for 5 large Latin American economies
and all major advanced and emerging economies of the world shows that the long-term
impact of a China GDP shock on the typical Latin American economy has increased by
three times since mid-1990s. At the same time, the long-term impact of a US GDP shock
has halved, while the transmission of shocks to Latin America and the rest of emerging Asia
(excluding China and India) GDP has not undergone any significant change. Contrary to
common wisdom, we find that these changes owe more to the changed impact of China on
Latin America's traditional and largest trading partners than to increased direct bilateral
trade linkages boosted by the decade-long commodity price boom. These findings help
to explain why Latin America did so well during the global crisis, but point to the risks
associated with a deceleration in China's economic growth in the future for both Latin
America and the rest of the world economy. The evidence reported also suggests that the
emergence of China as an important source of world growth might be the driver of the so
called "decoupling" of emerging markets business cycle from that of advanced economies
reported in the existing literature.
Keywords: China, GVAR, Great Recession, Emerging Markets, International Business
Cycle, Latin America, Trade linkages.
JEL Classification: C32, F44, E32, O54.
Beyond the DSGE straitjacket
M. Hashem Pesaran, Ron P. Smith
Abstract: Academic macroeconomics and the research department of central banks have come
to be dominated by Dynamic, Stochastic, General Equilibrium (DSGE) models based
on micro-foundations of optimising representative agents with rational expectations.
We argue that the dominance of this particular sort of DSGE and the resistance of
some in the profession to alternatives has become a straitjacket that restricts empirical
and theoretical experimentation and inhibits innovation and that the profession should
embrace a more flexible approach to macroeconometric modelling. We describe one
KeyWords: Macroeconometric models, DSGE, VARs, long run theory
JEL Classifications: C1, E1
Econometric Analysis of High Dimensional VARs Featuring a Dominant Unit
Alexander Chudik, M. Hashem Pesaran
Abstract: This paper extends the analysis of infinite dimensional vector autoregressive (IVAR) models proposed in Chudik and Pesaran (2011) to the case where one of the variables or the cross section units in the IVAR model is dominant or pervasive. It is an important extension from empirical as well theoretical perspectives. In the theory of networks a dominant unit is the centre node of a star network and arises as an efficient outcome of a distance-based utility model. Empirically, the extension poses a number of technical challenges that goes well beyond the analysis of IVAR models provided in Chudik and Pesaran. This is because the dominant unit influence the rest of the variables in the IVAR model both directly and indirectly, and its effects do not vanish as the dimension of the model (N) tends to infinity. The dominant unit acts as a dynamic factor in the regressions of the non-dominant units and yields an infinite order distributed lag relationship between the two types of units. Despite this it is shown that the effects of the dominant unit as well as those of the neighborhood units can be consistently estimated by running augmented least squares regressions that include distributed lag functions of the dominant unit and its neighbors (if any). The asymptotic distribution of the estimators is derived and their small sample properties investigated by means of Monte Carlo experiments.
Keywords: IVAR Models, Dominant Units, Star Networks, Large Panels, Weak and Strong Cross Section Dependence, Factor Models, Spatial Models.
JEL Classification: C10, C33, C51
An Accounting Method for Economic Growth
Abstract: As Chari et al. (2007) indicate, many growth theories explaining
frictions in real economies are equivalent to a competitive economy with
some exogenous taxes. Using this idea, I develop an accounting method
for identifying fundamental causes of economic growth. A two-sector
neoclassical growth model with taxes is used as a prototype economy, and
its equilibrium conditions define wedges. These wedges endogenously
determine the long run growth rate, which is exogenous and not
correlated with any other variables in a one-sector growth model.
Furthermore, the importance of wedges in explaining the long-run growth
rate can be evaluated through the prototype economy. Applying this
method to fifty countries reveals that, among seven wedges, two wedges
are important in explaining economic growth.
JEL Classifications: E13, O11, O41, O47