Quantitative Methods, E21 -Consumption|Saving < E2 -Consumption, Saving, Production, Employment, and Investment < E -Macroeconomics and Monetary Economics, E44 -Financial Markets and the Macroeconomy < E4 -Money and Interest Rates < E -Macroeconomics and Monetary Economics, O16 -Financial Markets|Saving

Keywords: Liquidity constraints, Asian developing countries, Error correction model

Testing liquidity constraints in ten Asian developing countries: an errorcorrection model approach

INTRODUCTION

During the 1960s and most of the 1970s, the majority of Asian countries had tightlyregulated and administratively-controlled financial systems.

Such common characteristics were manifested in interest rate restrictions, segmented financial markets and institutions, underdeveloped money and capital markets, credit allocation and control mechanisms and a variety of international capital and exchange controls. Among these financial distortions, interest rate ceilings on deposits and lending were important features. However, with the rapid advances in technology and communication and globalisation in financial markets worldwide, it became apparent that developing countries needed to be more flexible and responsive to the needs of their national and international economies. As a result, many Asian developing countries began to liberalise their financial system -in some cases, this began as early as the late 1970s.

Financial liberalisation has resulted in the development of a more sophisticated financial system not only in the developed countries but also in some developing countries. At times, such liberalisation has been associated with undesirable macroeconomic outcomes. [START_REF] Blundell-Wignall | Monetary Policy in Liberalised Financial Markets[END_REF] have pointed out that financial liberalisation will reduce liquidity constraints on consumption. With financial deregulation, households will be able to increase their consumption based on expected earnings, future wealth and relative prices. Current income and current liquid wealth are no longer such relevant factors for spending decisions. As a result, Spending decisions are likely to be more closely associated with permanent income and expected wealth. Consequently, the relationship between money supply (a major component of liquid wealth) and nominal demand will be affected, and ultimately the effectiveness of monetary policy will be reduced.

In a regulated financial environment, households often face limits on borrowing, that is, they are subject to liquidity constraints. Constrained households want to consume more, but are prevented from doing so by restrictions on their ability to borrow through credit rationing. This limitation implies that the options for consumption smoothing are limited. Consumption could be shifted into the future through saving, but increased consumption in the present may have to await increases in actual income. Therefore, consumption is more sensitive to current income in a regulated financial market. Empirical studies have shown that with heavily-regulated financial markets, consumption tends to track current income closely. In other words, consumption seems to respond to predictable changes in current income, that is, there is evidence of "excess sensitivity". Excess sensitivity has been associated with the existence of liquidity constraints. The findings by [START_REF] Blundell-Wignall | Financial Liberalization and the Permanent Income Hypothesis[END_REF] and [START_REF] Campbell | The Response of Consumption to Income: A Cross-Country Investigation[END_REF] that there is excess sensitivity of current consumption to disposable income in the OECD countries suggest the existence of liquidity constraints. Nevertheless, Blundell-Wignall et al. found that in several of the OECD countries liquidity constraints have been declining over time as a result of financial liberalisation.

Thus, one important implication of financial liberalisation is that liquidity constraints would be reduced. As a result of financial deregulation, borrowing constraints are lifted. Households will be more able to smooth their consumption relative to income through borrowing and thus increase their debt. Furthermore, empirical studies have

F o r P e e r R e v i e w
indicated that savings have fallen as a result of financial liberalisation due to the reduction in liquidity constraints (see [START_REF] Bayoumi | Financial Deregulation and Household Saving[END_REF][START_REF] Jappelli | Consumption and Capital Market Imperfections: An International Comparison[END_REF]. This is another undesirable effect of financial liberalisation.

Households that are not liquidity-constrained are able to base their consumption plans not only on current income but also on their future earnings and expected wealth. Thus, the effect of financial deregulation is that consumption should become more sensitive to factors such as wealth, future income (permanent income) and relative financial prices. As a result, the link between consumption and current income has become weaker in countries following the liberalisation of financial markets (see [START_REF] Blundell-Wignall | Financial Liberalization and the Permanent Income Hypothesis[END_REF]. This paper sets out to examine whether similar effects may be found in developing countries as well as in OECD.

Thus, the motivation of this paper is two-fold. The first objective is to investigate whether financial liberalisation has reduced liquidity constraints in ten Asian developing countries. The second is to employ current econometric standard practice of dealing with non-stationary time series data to determine the fraction of consumers that are liquidity constrained in these Asian countries. In relation to several developed countries, empirical studies have indicated that liquidity constraints have declined in importance during the 1980s, as financial systems have been deregulated (see [START_REF] Blundell-Wignall | Financial Liberalization and the Permanent Income Hypothesis[END_REF]. Following the work of [START_REF] Campbell | The Response of Consumption to Income: A Cross-Country Investigation[END_REF] and [START_REF] Blundell-Wignall | Financial Liberalization and the Permanent Income Hypothesis[END_REF], we explore this idea by allowing the 'excess sensitivity parameter', λ, to vary over time. Generally, a reduction in the size of the λ parameter signifies that liquidity constraints have been reduced as a result of financial liberalisation. The paper is organised as follows. In Section 2, we briefly review previous studies on testing liquidity constraint and the method for testing liquidity-constrained consumers. In Section 3, we present our results. The last section is our conclusion.

TESTING FOR LIQUIDITY CONSTRAINTS

There have been two main approaches to determine the fraction of liquidityconstrained consumers in an economy. The first is the Euler equation approach. This approach, which was proposed by [START_REF] Hall | Stochastic Implications of the Life Cycle-Permanent income hypothesis: Theory and Evidence[END_REF], is based on the estimation of the intertemporal first-order condition for the optimal choice of a fully forward-looking representative consumer. The second is the error-correction model approach which was popularised by [START_REF] Davidson | Econometric Modelling of the Aggregate Time-Series Relationship between Consumers' Expenditure and Income in the United Kingdom[END_REF] and Hendry and Ungern-Sternberg (1981).

Both approaches have their own merits, as discussed, for example, by [START_REF] Deaton | Understanding Consumption[END_REF], [START_REF] Favero | Error Correction and Forward Looking Models for UK Consumers' Expenditure[END_REF] and [START_REF] Muellbauer | The Assessment: Consumer Expenditure[END_REF], but Hendry and Davison (1981) and [START_REF] Favero | Error Correction and Forward Looking Models for UK Consumers' Expenditure[END_REF] argue persuasively against the Euler equation approach. For the purpose of this study, the approach is based on the single-equation error-correction methodology advocated by [START_REF] Hendry | Econometric Modelling: The Consumption Function in Retrospect[END_REF] in empirical time series research. This type of model can be interpreted as a structural representation of dynamic adjustment towards some equilibrium about which economic theory can be informative, while short-run dynamics are data-based determined.

Modelling the consumption function using the error-correction approach was first introduced by Davidson et al. (1978, hereafter DHSY). The basic DHSY model is given as follows 1 ,

F o r P e e r R e v i e w ∆c t = θ 0 + θ 1 ∆y t + θ 2 (c t-1 -y t-1 ) + ε t (1)
where c denotes consumption and y disposable income. Estimation of equation ( 1) also implies a direct test for cointegration between consumption and income. [START_REF] Banerjee | Co-Integration, Error-Correction and the Econometric Analysis of Non-Stationary Data[END_REF] and [START_REF] Kremers | The Power of Cointegration Tests[END_REF] have shown that the statistical significance of the coefficient of the error-correction term, θ 2 can be interpreted as evidence of cointegration. According to [START_REF] Blundell-Wignall | Financial Liberalization and the Permanent Income Hypothesis[END_REF] and [START_REF] Chah | Liquidity Constraints and Intertemporal Consumer Optimization: Theory and Evidence from Durable Goods[END_REF], the significance of θ 1 and θ 2 in equation ( 1) suggest that cointegration between consumption and income implies support for the liquidity constraints hypothesis. Thus, the significance of θ 1 (equivalent to λ) is the test for rule-of-thumb behaviour (myopia) and therefore can be used to estimate the fraction of consumers that are liquidity constrained (see also [START_REF] Campbell | The Response of Consumption to Income: A Cross-Country Investigation[END_REF]Blundell-Wignal et al., 1995;[START_REF] Agell | Does Financial Deregulation Cause a Consumption Boom[END_REF].

In this study, we derived our final error-correction model from the following general autoregressive distributed lag (ARDL) consumption function (see for example, [START_REF] Hendry | Dynamic Specification in Handbook of Econometrics[END_REF],

c t = α + j k = ∑ 0 β j y t-j + j m = ∑ 1 φ j c t-j + ε t (2)
where ε t is the error term. By adding and subtracting lags of the variables, equation

(2) may be reparameterised without loss of generality as the following unrestricted error-correction model ,

F o r P e e r R e v i e w ∆c t = α + β 0 ∆y t + j k = - ∑ 1 1 β j ∆y t-j + j m = - ∑ 1 1 φ j ∆c t-j + δ 1 c t-1 + δ 2 y t-1 + ε t (3)
With minor algebraic manipulation, equation (3) may be rewritten so as to incorporate the long-run solution, c t = γy t , directly as follows 2

∆c t = α + β 0 ∆y t + j k = - ∑ 1 1 β j ∆y t-j + j m = - ∑ 1 1 φ j ∆c t-j + δecm t-1 + ε t (4)
where the error-correction term, ecm t-1 is equal to (c -γy) t-1 . If δ is significant and negative, this indicates that consumers adjust consumption in response to short-run changes in income, as well as to previous disequilibria (c t-1 -γy t-1 ), which can be interpreted as a feedback response to obtain a desired long-run condition. The parameter β 0 (equivalent to λ in the Euler equation in Blundell-Wignal et al., 1995) is then used to measure the fraction of consumers who are liquidity-constrained.

Compared with the error-correction model of [START_REF] Campbell | The Response of Consumption to Income: A Cross-Country Investigation[END_REF], Blundell-Wignal et al. (1995) and [START_REF] Agell | Does Financial Deregulation Cause a Consumption Boom[END_REF], our equation ( 4) is a more general error-correction model with lagged consumption and income as additional explanatory variables.

Sources of Data

The Asian developing countries included in the study are Indonesia, Malaysia, Myanmar, Nepal, Philippines, Singapore, South Korea, Sri Lanka, Taiwan and

ESTIMATION AND RESULTS

Before we estimate equation ( 4), we have tested each series for unit roots and for cointegration between consumption and income. As reported in Table 1, our results

clearly indicate that c t and y t are all integrated of order one. The cointegration test based on the Engle-Granger two-step procedure suggests that only in the cases of South Korea and Sri Lanka can the null of no cointegration between c t and y t be rejected.

We next proceed with a direct test for cointegration using the error-correction model as suggested by [START_REF] Kremers | The Power of Cointegration Tests[END_REF]. The results are presented in Table 2. The final parsimonious error-correction models were searched between the first-through fourth-order ARDL model using the Hendry's general to specific modelling approach. In all cases, the final selected ARDL model passes the diagnostic tests of no serial correlation, normality of residuals and homoscedasticity. 4 Further, we have tested for weak exogeneity of income in the error-correction model. In order to test for the weak exogeneity of y t , we have estimated the following equation, 5

∆y t = π 0 + i= ∑ 1 4 π 1 ∆y t-i + i= ∑ 1 4 π 2 ∆c t-i + i= ∑ 1 4 π 3 ∆x t-i + i= ∑ 1 4 π 4 ∆pop t-i + π 5 ecm t-1 + ω t (5) F o r P e e r R e v i e

w

The weak exogeneity test procedure using equation ( 5) is to test for the significance of the ecm t-1 coefficient, π 5 . If π 5 is not significantly different from zero then the income process is weakly exogenous with respect to the long-run parameters (see [START_REF] Urbain | On Weak Exogeneity in Error Correction Models[END_REF][START_REF] Johansen | Testing Weak Exogeneity and the Order of Cointegration in UK Money Demand[END_REF]. Our results for weak exogeneity tests suggest that except in the case of Taiwan, income in nine Asian developing countries investigated is weakly exogenous. This implies that income in nine of the Asian countries is free from simultaneity bias, so the use of single-equation estimation is justified. 6 We now turn to the results of our error-correction model. Our variables of interest are the significance of ∆y t and the ecm t-1 term. In all cases, both ∆y t and ecm t-1 are significantly different from zero at the five percent level. 7 The ecm t-1 variable has the correct negative sign. As pointed out by [START_REF] Chah | Liquidity Constraints and Intertemporal Consumer Optimization: Theory and Evidence from Durable Goods[END_REF] and early 1990s. 8 Thus, if deregulation played a role, we would expect to see a reduction in the point estimate of λ in the second sub-sample period.

Table 3 presents the results from estimating equations ( 4) for the two sub-sample periods. Our results from the error-correction model suggest that both the estimates of λ and the ecm t-1 term are significantly different from zero in all ten Asian countries investigated. In fact the two parameters are statistically significant at the five percent level in both time periods. Furthermore, in all cases the ecm t-1 term has the correct negative sign implying that consumption and income are strongly cointegrated in both time periods. This evidence provides support for the existence of liquidity constraints in the ten Asian developing countries studied. As to the size of the estimates of λ, only in the cases of South Korea, Sri Lanka and Taiwan do the estimates of λ fall between the 1950s/70s and the 1980s/90s: by 73 percent, 24 percent and 20 percent respectively. However, for other countries, the estimate of λ has either remained unchanged (in the cases of Indonesia, Nepal, Philippines, Singapore and Thailand) or increased (in the cases of Malaysia and Myanmar) over time.

CONCLUSIONS

Financial liberalisation has been recognised as an important step towards achieving economic progress by allowing financial markets to be determined by market forces.

The proliferation of financial intermediaries, financial instruments and the development of money and capital markets will enhance the formation of an efficient and sophisticated financial system. Nevertheless, one important implication for financial liberalisation is to reduce liquidity constraints. As a result of financial deregulation, households will be able to smooth their consumption relative to income through borrowing as borrowing constraints were lifted. The ability of households to borrow and adjust their financial portfolios has important implications for monetary aggregates and consequently for the conduct of monetary policy. In order to increase their current consumption, households will increase their borrowing (using available financial or physical assets as collateral) or adjust their financial portfolios or relinquish part of their accumulated wealth. As a result of financial liberalisation consumption becomes more sensitive to wealth, and the relationship between consumption and current income will be weakened. Consequently, we should observe that the relationship between monetary aggregates and current income will also be weakened in financially liberalised economies.

The purpose of the present study is to investigate whether financial liberalisation has reduced liquidity constraints in ten Asian developing countries. To do this, we have estimated an error-correction model to determine whether the estimates of the λ's have been reduced in the deregulation era. Our results suggest that it is only in the cases of South Korea, Sri Lanka and Taiwan that the estimates of the λ's was reduced in magnitude in the 1980s/90s, compared to the earlier sub-sample period.

For the 1980s/90s sub-sample period, the fraction of consumers that were liquidity constrained in South Korea, Sri Lanka and Taiwan are 22 percent, 68 percent and 37 percent respectively. The estimates of the λ's for other Asian developing countries investigated, have either remain unchanged or increased in the latter sub-sample periods. Despite the reductions in the estimates of λ's in several of these countries, the longrun relationship between consumption and income has been strong. In all the Asian developing countries investigated, the ecm t-1 term is negative and significantly different from zero and in most cases at the one percent level in both sub-sample periods. This implies that consumption and current income are strongly cointegrated.

The finding for cointegration between consumption and income signifies that there will be a stable long-run relationship between the monetary aggregates and income and consequently, monetary aggregates will be useful for the purpose of monetary policy action in these Asian countries.

  Thailand. The model is estimated country by country using annual data, with the sample period covering from 1950 to 1994.3 The variables included are: (a) real private consumption per capita to measure household consumption. (b) real income measure disposable income, where income is measured by GDP. (c) All nominal variables are deflated using the Consumer Price Index (CPI). Data were collected from various issues of International Financial Statistics published by International Monetary Fund. All variables were transformed into logarithms.

  this provides supporting evidence for the presence of liquidity constraints for each country investigated. The fraction of liquidity-constrained consumers estimated from the error-correction model range from 0.25 in the case of Taiwan, to 0.98 in the case of Nepal. Our next question is: did λ change during the deregulation era? If the financial liberalisation process seen in financial markets has caused liquidity constraints to be progressively relaxed, then estimating equations (4) for successive time periods should tend to indicate a reduction in the λ parameter. In this study, we follow Blundell-Wignal et al. (1995) by estimating separate λ equations for different time periods. We have divided the time period into two sub-sample periods of 1950s/70s and 1980s/90s for our tests. In all of the Asian countries considered in this study, financial liberalisation have been more active in the late 1980s

Table 2 :

 2 Results of Error-Correction Model

	Variables	Indonesia	Malaysia	Myanmar	Nepal	Philippines
	A. Error-correction models
	Constant	0.0224	0.0545	-0.4374	-0.0405	0.8750
		(0.6953)	(0.9035)	(1.5146)	(0.1947)	(6.7476)*
	∆yt	0.4065	0.5430	0.4928	0.9812	0.3550
		(4.5920)*	(6.8225)*	(5.1538)*	(15.758)*	(5.2446)*
	ecmt-1	-0.5424	-0.3251	-0.3841	-0.1237	-0.5640
		(4.3706)*	(2.9135)*	(5.5353)*	(1.1812)	(6.3646)*
	∆ct-1	0.0681	0.2454		-0.0728
		(0.5060)	(2.6744)*		(1.1840)
	∆ct-2		0.0471
			(0.4707)
	R-squared	0.486	0.707	0.479	0.908	0.550
	SER	0.042	0.027	0.065	0.025	0.026
	Dw	1.864	1.744	1.634	2.133	1.521
	Weak exogeneity:
	t: π5	-0.1738	0.0639	-0.4161	0.7467	-0.1781
	B. Underlying Autoregressive Distributed Lag (ARDL) models
		ARDL (2,0)	ARDL (3,1)	ARDL (1,0)	ARDL (2,1)	ARDL (1,0)
	Constant	0.0224	0.0545	-0.4374	-0.0405	0.8750
		(0.6953)	(0.9035)	(1.5146)	(0.1947)	(6.7476)*
	ct-1	0.5257	0.9202	0.6158	0.8034	0.4359
		(3.2316)*	(6.4389)*	(8.8745)*	(6.7131)*	(4.9184)*
	ct-2	-0.0681	-0.1982		0.0728
		(0.5060)	(1.2889)		(1.1840)
	ct-3		-0.0471
			(0.4707)
	yt	0.4065	0.5430	0.4928	0.9812	0.3550
		(4.5920)*	(6.8225)*	(5.1538)*	(15.758)*	(5.2446)*
	yt-1		-0.2843		-0.8543
			(2.5716)*		(6.6548)*
	R-squared	0.988	0.993	0.835	0.973	0.969
	SER	0.042	0.027	0.065	0.025	0.026
	DW	1.864	1.744	1.634	2.133	1.521
	LM (1)	0.077	0.466	1.496	0.315	2.478
		[0.781]	[0.494]	[0.221]	[0.574]	[0.115]
	Norm (2)	1.279	3.864	1.202	3.638	6.086
		[0.527]	[0.145]	[0.548]	[0.162]	[0.048]*
	ARCH (2)	0.580	0.422	1.775	0.242	0.831
		[0.446]	[0.516]	[0.183]	[0.622]	[0.362]
	Notes: ecmt-1 is the error-correction term. SER and DW denote standard error of regression and Durbin-Watson statistic
	respectively. LM (1) and ARCH (1) are Lagrange multiplier tests for first-order serial correlation and autoregressive
	conditional heteroskedasticity. Norm (2) is a test for the normality of the residuals. All three tests are asymptoticlly distributed
	as χ-square. Figures in parentheses (.) and square brackets [.] are t-statistics and p-values respectively. Asterisk (*) denotes
	statistically significant at five percent level.

Table 2 :

 2 Results of Error-Correction Model (continued)Notes: ecmt-1 is the error-correction term. SER and DW denote standard error of regression and Durbin-Watson statistic respectively. LM (1) and ARCH (1) are Lagrange multiplier tests for first-order serial correlation and autoregressive conditional heteroskedasticity. Norm (2) is a test for the normality of the residuals. All three tests are asymptoticlly distributed as χ-square. Figures in parentheses (.) and square brackets[.] are t-statistics and p-values respectively. Asterisk (*) denotes statistically significant at five percent level.

	Variables	Singapore	South Korea	Sri Lanka	Taiwan	Thailand
	A. Error-correction models
	Constant	0.2045	0.0434	-0.3921	-0.1273	-0.3997
		(2.6386)*	(3.3592)*	(6.5777)*	(3.1836)*	(6.9276)*
	∆yt	0.6536	0.6879	0.8556	0.2535	0.4725
		(10.338)*	(9.9273)*	(9.0482)*	(5.1427)*	(8.8317)*
	ecmt-1	-0.2050	-0.8343	-0.8219	-0.2800	-0.5768
		(3.0579)*	(9.8210)*	(8.9038)*	(4.7285)*	(8.5767)*
	∆ct-1	0.5733		0.2779	0.0623	-0.0716
		(3.6224)*		(2.9966)*	(0.4853)	(0.9159)
	∆ct-2				-0.0790	-0.0807
					(0.6098)	(1.0283)
	∆ct-3					0.1307
						(1.8334)
	∆yt-1	-0.4232
		(3.6925)*
	R-squared	0.869	0.724	0.680	0.502	0.748
	SER	0.016	0.032	0.030	0.031	0.019
	Dw	1.886	1.475	1.835	1.750	2.168
	Weak exogeneity:
	t: π5	-1.6187	0.1319	0.0315	-2.0933*	-0.9007
	B. Underlying Autoregressive Distributed Lag (ARDL) models
		ARDL (2,2)	ARDL (1,0)	ARDL (2,0)	ARDL (3,0)	ARDL (4,0)
	Constant	0.2045	0.0434	-0.3921	-0.1273	-0.3997
		(2.6386)*	(3.3592)*	(6.5777)*	(3.1836)*	(6.9276)*
	ct-1	1.3683	0.1656	0.4560	0.7823	0.3515
		(8.8770)*	(1.9492)	(4.1191)*	(5.2333)*	(3.8013)*
	ct-2	-0.5733		-0.2779	-0.1414	-0.0090
		(3.6224)*		(2.9966)*	(0.7262)	(0.0921)
	ct-3				0.0790	0.2114
					(0.6098)	(2.2856)*
	ct-4					-0.1307
						(1.8334)
	yt	0.6536	0.6879	0.8556	0.2535	0.4725
		(10.338)*	(9.9273)*	(9.0482)*	(5.1427)*	(8.8317)*
	yt-1	-0.9400
		(7.3501)*
	yt-2	0.4232
		(3.6925)*
	R-squared	0.998	0.998	0.996	0.997	0.997
	SER	0.016	0.032	0.030	0.031	0.019
	DW	1.886	1.475	1.835	1.750	2.168
	LM (1)	0.047	3.256	0.131	2.055	0.871
		[0.827]	[0.071]	[0.716]	[0.152]	[0.351]
	Norm (2)	2.313	1.941	0.736	0.255	3.721
		[0.315]	[0.379]	[0.692]	[0.880]	[0.156]
	ARCH (2)	0.575	1.060	0.569	2.781	1.016
		[0.448]	[0.303]	[0.451]	[0.095]	[0.313]

Editorial Office, Dept of Economics, Warwick University, Coventry CV4 7AL, UKSubmitted Manuscript

Editorial Office, Dept of Economics, Warwick University, Coventry CV4 7AL, UK Submitted Manuscript F o r P e e r R e v i e w Notes: The relevant tests are derived from the OLS estimation of the following augmented Dickey-Fuller (ADF) regression:

where ∆ is the difference operator, t is a linear time trend and ν is the disturbance term. The hypothesis that a series contains a unit root is tested by H0 : β = 0 while the hypothesis that the series is non-stationary with a stochastic trend rather than a deterministic time trend is tested by H0 : b = -β. Rejection of the latter hypothesis suggests the existence of a deterministic trend. ττ is the t-statistic for testing the significance of β when a time trend is included in the above equation while τµ when time trend is excluded. The lag length n, was chosen based on Schwarz Bayesian Criterion (SBC). The calculated statistics are those computed in MacKinnon (1991). The critical values at 5 percent are -3.62 (Indonesia), -3.56 (Malaysia, Nepal), -3.53 (Myanmar, Philippines, South Korea, Sri Lanka, Taiwan, Thailand), -3.57 (Singapore) for ττ. When testing for first-differences of the series, time trend was dropped from the above regression equation. The critical values for τµ at 5 percent level are -3.00 (Indonesia), -2.96 (Malaysia, Nepal), -2.94 (Myanmar, Philippines, South Korea, Sri Lanka, Taiwan, Thailand), and -2.97 (Singapore). The critical values for cointegration tests at 5 percent level are -3.61 (Indonesia), -3.53 (Malaysia, Nepal), -3.50 (Myanmar, Philippines, South Korea, Sri Lanka, Taiwan, Thailand), and -3.55 (Singapore).

Editorial Office, Dept of Economics, Warwick University, Coventry CV4 7AL, UK

Submitted Manuscript

F o r P e e r R e v i e w Indonesia (1966-1994), Malaysia (1958-1994), Myanmar (1950-1994), Nepal (1958-1994), Philippines (1950-1994), Singapore (1960-1994), South Korea (1953-1994), Sri Lanka (1950-1994), Taiwan (1950-1994) and Thailand (1952-1994). GIV (2SLS) denotes Generalised Instrumental Variable (Two Stage Least Squares) method. ARDL/ECM denotes Autoregressive Distributed Lag/Error-correction model. Asterisk (*) denotes statistically significant at five percent level.

Editorial Office, Dept of Economics, Warwick University, Coventry CV4 7AL, UK

Submitted Manuscript


Joan Costa-Font

Panos Kanavos

Joan Rovira

Dr Joan Costa

pharmaceutical expenditure and access to drugs in Catalonia

Keywords: pharmaceutical expenditure, demand for pharmaceuticals, cost containment, user charges and cost-sharing, household budget surveys, Catalonia, Spain. JEL classifications: I11, I18

Determinants of out-of-pocket pharmaceutical expenditure and access to drugs in Catalonia

Introduction

Pharmaceutical spending is the most dynamic component of health care expenditure in most European Union (EU) countries [START_REF] Mossialos | Cost Containment in the European Union: An Overview[END_REF]. However, research on the determinants of pharmaceutical expenditure is still limited. Studies indicate that, in addition to price regulation, pharmaceutical expenditure is sensitive to cost sharing [START_REF] Newhouse | Free for All? Lessons from the RAND Health Care Insurance Experiment[END_REF]. The understanding of the causes of pharmaceutical expenditure requires an examination of the process leading to the demand for medicines. Conceptually, the demand for prescription drugs results from the physician-patient agency relationship. The physician takes into account the patient's utility and, arguably, the costs of prescribing to the health insurer as well as the patient in the presence of cost sharing arrangements [START_REF] Hellerstein | The Demand for Post-Patent Prescription Pharmaceuticals[END_REF][START_REF] Dranove | Medicaid Drug Formulary Restrictions[END_REF]. Patient insurance is argued to affect doctor's prescribing decision as well as patient consumption [START_REF] Pavcnik | Do Pharmaceutical Prices Respond to Insurance[END_REF]. Indeed, the physician may be acting as a perfect agent for the patient; he might not be a perfect agent for the (public or private) insurer (Feldstein, 1976).

One of the most frequently used tools to control utilisation of health care resources, and, indirectly, health care expenditure, is cost-sharing, whereby the patient bears part of or the entire cost of health care use. Cost sharing has been found to reduce health expenditure with limited effects on health (Manning et al, 1993;[START_REF] Newhouse | Free for All? Lessons from the RAND Health Care Insurance Experiment[END_REF]. Additional research indicates that high cost-sharing rates increase compliance with medications [START_REF] Dor | Does cost sharing affect compliance? The Case of Prescription Drugs[END_REF]. Further evidence suggests that most of the effects of cost sharing are determined by the numbers of prescriptions filled (Leibowitz et al,1986). Indeed, the rationale for introducing co-payments for pharmaceuticals relates to the pursuit of controlling potential physician/consumer moral hazard in prescribing/consuming drugs without bearing the costs for the health system [START_REF] Cossley | The effects of drugs subsidies on out-of pocket prescription drug expenditures: regional evidence from Canada[END_REF]. Even though rising costs may justify insurance coverage to reduce the burden of out-of-pocket drug spending (Stuart et al, 2000) significant moral hazard effects may induce individual drug consumption to rise. Nonetheless to reduce moral hazard, cost sharing is employed by most of European health systems either in the form of a fixed fee (Germany (until end-2003), Ireland and the United Kingdom) or co-insurance, whence the insuree pays a proportion of the price (Spain, Greece, France), or a deductible, where the insuree pays a fixed amount out-of-pocket before health insurance coverage kicks in (Sweden, Denmark, Norway, Finland), or, most often, a combination of the above. Yet, the effectiveness of co-payments in containing expenditure and improving system efficiency is disputed (Tamblyn et al, 2001). In Spain, effective cost sharing in pharmaceuticals has declined progressively between 1986-2000 while real pharmaceutical expenditure has 1 shows. There is also some evidence arguing that elderly patients are using their exemption rights under the Spanish NHS to fill prescriptions on behalf of their relatives in order not to pay the statutory co-payment (Costa-Font and [START_REF] Costa-Font | Regulatory Ambivalence and the Limitations of Pharmaceutical Policy in Spain[END_REF]López-Bastida and Mossialos, 2000). This feature points to the need of examining the determinants of drug consumption and expenditure to assess which predictors have an impact on household consumption, and whether co-payment determinants, such as age and disability significantly influence expenditure. Furthermore, in examining the association between income and expenditure on the one hand and demand for drugs on the other, one might determine whether the current co-payment structure might determine access to drugs and expenditure patterns. Co-payment structures not linked to income could lead to inequality in accessing medicines. Evidence suggests that subsidising prescription drugs to elderly in Canada turns out to be less beneficial compared with what would have been if the same amounts had been put into a programme of fixed cash transfers paid equally to all households [START_REF] Alan | The effect of drug subsidies on out-of -pocket prescription drug expenditures by seniors: regional evidence from Canada[END_REF].

[INSERT TABLE 1 ABOUT HERE]

Previous studies on the demand for health care in Spain from household budget surveys have tended to exclude the demand for pharmaceuticals, mainly because the existence of statutory patient co-payments limits the likelihood of identifying its influence with accuracy (López , 1998). Only one study estimated the effects of co-payments using aggregate data and found a low-price elasticity [START_REF] Puig | Gasto Farmaceutrico en España: efectos de la participación en el coste[END_REF]. Evidence from the US suggests that insurance coverage for pharmaceuticals increases the use of and expenditure on prescription drugs, and may lead to a reduction of out-of pocket expenditures [START_REF] Lillard | Insurance coverage for prescription drugs[END_REF][START_REF] Coulson | Estimating the moral hazard effect of supplemental medical insurance in the demand for prescription drugs by the elderly[END_REF]. However, there is still little evidence of this phenomenon in European countries including Spain.

In this context, the objectives of the paper are twofold: first, to estimate the impact of the variables influencing cost sharing and the individual demand for pharmaceuticals.

Second, to analyse whether demographic, socio-economic and health status characteristics influence the out-of-pocket demand and expenditure for pharmaceuticals along with the influence of self-medication. Therefore, the dependent variables are (a) individually adjusted household pharmaceutical expenditure and (b) whether household respondents have consumed drugs in the last month. Thus, this study deals with the determinants of the access to pharmaceuticals and out-of-pocket expenditure along with other potential determinants F o r P e e r R e v i e w 5 such as demographics, the impact of self-medication, socio-economic and health status variables, and the presence or not of chronic conditions among respondents. We employ a two-equation model to estimate the determinants of pharmaceutical expenditure due to the censoring nature of the data. In explaining drug use we also employ a sample selection model (Heckman, 1978) to capture the potential influence of physician gate-keeping in accessing prescription medicines. From the variables included in the model we are in a position to investigate the influence of cost sharing policies, self-medication and income effects on the demand for pharmaceuticals.

Section two provides a description of the market for medicines in Spain as well as the regulatory features of the Spanish pharmaceutical market. Section three develops the theoretical model and the expected determinants. Section four analyses the empirical specification and section five discusses the results. Finally, section six draws the main conclusions.

The Spanish Pharmaceutical Market and Regulation

The Spanish National Health System (NHS) is tax-funded and provides universal and free health care coverage, with some exceptions such as non-refundable co-payments for prescribed pharmaceuticals. The general rate of co-payment for drugs has remained at 40% since the early 1980s. However, prescription medicines for pensioners and medicines consumed in hospitals are provided free of charge, and chronically ill patients under 65 (for example, diabetics) only pay 10% of their prescription drug costs, with a price cap of €2.64 per prescription item. Private health care outlays account for 20% of total health care outlays in Spain. Approximately 15% of the population has supplementary private health insurance, which does not cover prescription drugs. In the early 1980s the NHS underwent radical reform, with the gradual introduction of a decentralised model involving the creation of 17 autonomous regional health services, corresponding to the 17 Autonomous Communities (ACs) into which Spain is divided. These regional bodies have political responsibility for health care, although, with the exception of Navarre and the Basque Country, they remain financially dependent on the central government.

The market for pharmaceuticals in Spain comprises three main segments: (i) over-thecounter (OTC) medicines for which consumers pay the entire cost out-of-pocket (which may include vitamins and other supplements), (ii) prescription medicines (patented novel medicines, branded and unbranded generics) sold under NHS GP prescription which are subjected to co-payments depending on patient characteristics and (iii) medicines purchased Prescription drugs account for approximately 92% of total pharmaceutical expenditure and 85.5% of the total market by volume, with OTCs accounting for the remainder (Costa-Font and Puig-Junoy, 2004). Although the Spanish NHS provides comprehensive drug coverage, patients purchase a significant proportion of all drugs consumed as OTC. OTCs are mainly analgesics (19% of total OTC expenditure), cough and cold preparations (17%), respiratory system drugs (16%), dermatological drugs (11.9%), and laxatives, vitamins and supplements (6%). The prescription market dominates pharmacists' sales. On average, prescription drugs are three times more expensive than OTCs 1 . In the 1990s, there was some debate on the hypothetical effects of cost-containment policies (such as introducing a negative list and implementing additional barriers to obtaining prescriptions for less expensive drugs) on the development of the OTC market, since OTCs can be advertised directly to the consumers whereas prescription drugs cannot. However, the volume of OTCs has remained stable over time; though expenditure increased by 7.5% between 1990 and 2001, the market for prescription drugs increased significantly in terms of both number of packs (1.5% increase annually) and sales growth (10.7% increase) 2 . In an environment where direct-to-consumer (DTC) advertising is banned for prescription drugs, promotional campaigns that are indirectly linked with prescription-only medicines focus on GPs only, whereas they do focus on the general public through TV advertising in the OTC market.

Pharmaceutical regulation comprises measures on the supply-, proxy demand-and demand-side. Supply-side policies comprise intervention on the prices of medicines, whereas proxy demand-side policies deal with the prescribing and dispensing of medicines. Finally, demand-side policies target patients, through cost sharing. The central government in Madrid is responsible for setting prices of medicines and determining the overall cost sharing and reimbursement strategy at national level the latter with the participation of representatives from the 17 autonomous communities, whereas the regions, including Catalonia, are responsible for implementing national policy and paying providers within their jurisdiction.

Experiments with proxy demand policies, for instance on prescribing, have been observed at regional level. Controlling pharmaceutical expenditure is one of the main policy priorities of the Spanish NHS. Pharmaceutical expenditure accounts for 1.2% of GDP and has risen systematically since the establishment of the NHS in 1986. In the 1990s, expenditure growth has been driven by volume increases rather than pharmaceutical price inflation (Costa-Font 1 Average (per pack) prices were €6.07 for prescription drugs and €2.05 for OTCs in 2001. and [START_REF] Costa-Font | Regulatory Ambivalence and the Limitations of Pharmaceutical Policy in Spain[END_REF]. Decentralisation of the Spanish NHS has meant that each of the 17 autonomous regions has had significant flexibility in organising and delivering health services. Catalonia was the first autonomous region to have obtained responsibility for health care organisation and delivery in 1981. Regional health services are only partially responsible for pharmaceutical care, especially in promoting generic pharmaceuticals and prescribing policies, whereas the central government, through the Ministry of Health (MoH) and other interdepartmental commissions and agencies, undertakes drug registration and licensing and sets drug prices. Pharmaceutical expenditure accounts for roughly 20% of total public health care expenditure in Spain, making this share one of the highest in the EU.

Supply-side policies and pricing of pharmaceuticals

Price regulation of pharmaceuticals is mainly based on the decision of a Commission at the Spanish Ministry of Health and Consumption (MoHC) that determines the maximum reimbursable price for every pharmaceutical speciality. This price includes generics but excludes OTCs. Drug prices differ depending on the setting in which they are sold. For instance, drugs sold to hospitals, attract discounts to payers that are explicitly contemplated in the maximum price setting that the MoHC undertakes. Drugs consumed on an outpatient basis include wholesale and retail margins on top of the ex-manufacturer price. With the passing of the General Health Act in 1986, GPs became integrated into the public network. The act improved the general public's access to primary care. However, it has also led to an increase in the number of GP visits, a development likely to have had some influence on the number of prescriptions. As GPs are paid on a fixed salary basis, they have few incentives to prescribe efficiently, and it was not until the 1990s that some contracts with 2 It is has also been estimated that the 6% of prescription drugs are dispensed without a prescription. Catalonia (1999) to encourage primary care physicians to prescribe drugs "cost-effectively" and increase their prescribing of generics; GPs were also subjected to stricter control over both efficiency and quality. Furthermore, primary care pharmacists were established in 1995 to monitor prescribing patterns and to offer advice to consumers on suitable pharmaceutical treatments. 3Prescribing policies are based on practice guidelines developed at the regional level.

Physicians -both GPs and specialists-are paid a salary partly determined by incentives linked to prescribing quality. Generics are being extensively promoted through a reference price system albeit penetration is less that 6% of total market volume. Proxy demand-side policies implemented in Spain mainly refer to the introduction of stricter prescribing controls, although there is still evidence of significant clinical variability, the introduction of de-listing policies in the form of "negative lists" for drugs for minor ailments, and the establishment of fixed budgets for pharmaceutical spending. Despite the proliferation of policies on the proxydemand, the robustness with which they have been implemented and their effectiveness in containing pharmaceutical costs have been disputed in the literature (Lopez and Mossialos, 2000).

Although the statutory nominal co-payment rate for pharmaceuticals has been 40%

for most drugs since the early 1980s, the effective co-payment rate (i.e. the rate taking into account exemptions and log-term illnesses) has declined from 15% in 1985 to 7% in 2002, and this was deemed responsible for an increase by 0.4% annually in the share of pharmaceuticals in total public health care expenditure during that period (Costa-Font and [START_REF] Costa-Font | Regulatory Ambivalence and the Limitations of Pharmaceutical Policy in Spain[END_REF]. As a result, cost sharing levels in Spain are among the lowest in the EU.

Simultaneously, the share of pharmaceutical spending of the retired population (who amount to around 15% of the total population and are exempt from co-payments) practically doubled (from 39% to 72%) between 1985 and 2002. As Table 1 shows, the share of retired consumers increased significantly from around 60% at the end of the 1980s to 72% in 2002.

This partially reflects an increase in the number of retirees, who have significantly higher

The model

Standard economic theory suggests that the demand for pharmaceuticals derives from the individual demand for health care following the Grossman tradition [START_REF] Grossman | On the Concept of Health Capital and the Demand for Health[END_REF].

Agents employ time and health care inputs -both intangible (medical care) and tangible (pharmaceuticals) -to fulfil demand for health. Let us follow state-dependent demand analysis and assume that each household/individual i maximises a utility function subject to a budget constraint. As a result an indirect utility function can be isolated that will depend on the health status of the individual whether sick or not. If sick, the individual will consume a certain drug (k) depending on the percentage of individual income (y) it absorbs (which would be reduced or eliminated by means of existing co-payments), prices (p) of drugs and substitute treatments, and other characteristics (z). However, when the individual is healthy, the value of drugs is null and thus utility can be reduced to individual income as follows:

= healthy if ) ( sick if ) , , ( i ik i k i ik hi x v z p x v v (1)
where i y is the total expenditure per household that is assumed to be equal to disposable income, k p refers to prices and i z is a vector of household characteristics. Under the Roy's identity, following [START_REF] Alan | The effect of drug subsidies on out-of -pocket prescription drug expenditures by seniors: regional evidence from Canada[END_REF], a percentage increase in prices under the assumption of sickness leads to:

i k ik k ik y v q p v = (2)
where ik q is the quantity consumed of drug k by the household i, so that a rise in prices will reduce welfare proportionally to the income reduction from facing the drug prices times the quantity of drugs consumed. Accordingly, the demand for drugs will be constrained by the following explanatory variables: health status ( i h ) as determining need and sickness, income ( i y ) which influences the capacity to cope with larger cost-sharing and prices of drugs, and ( ik p ) which can be approximated by the influence of proxy variables such as 'age' and 'disability' although part of the effects might be associated with health deterioration. Finally, our model includes a number of specific variables affecting the consumption of medical and pharmaceutical products ( i z ). Those variables include education attainment, [START_REF] Kenkel | Health Behaviour, Health Knowledge amd Schooling[END_REF], and self-medication, the latter determining the extent to which an individual might pay for medicines out-of-pocket. Therefore, we can model the demand for drugs ) ( ik q as dependent on those variables as follows: ) , , , (

i i ik i ik z y p h q q = (3)
where the expected marginal effects would be 0 , 0 , 0

i ik ik ik i ik y q p q h q
while the effect of specific determinants might exhibit different signs. ) and the error term ( µ ). Furthermore, given the co-payment structure we just observe the out-of-pocket expenditure rather than total expenditure. Therefore, we proceed by formulating a two-stage model that takes into account the censored nature of the data as follows:

Household determinants of pharmaceutical expenditure

0 0 Q if 0 * * * * > = = + = Q if Q Q Q X Q i µ (4)
4 Drugs are products subject to substantial product and price differentiation; therefore it is impossible to estimate adequate household specific price index. This specification allows accounting for a number of zero responses appearing due to the existence of the cost sharing policies (not paying the co-payment versus paying the copayment) and X refers to all explanatory variables. In a first stage we examine the determinants of some drug consumption using a probit model

) / 0 ( X Q pr >
and in a second

stage we examine ) / 0 / ( X Q Q E > .
If Q measures household out-of-pocket expenditure on pharmaceuticals, the coefficient in logs is interpreted as elasticities5 . Because information on the controlling variable (health status) is at the individual level we have excluded this variable from the expenditure function, which will serve, jointly with self-medication, as an identification variable. Furthermore, because drugs are not consumed on a day-to-day basis, one might expect to find a censoring problem. Therefore, we employed a two-part model where in a first stage we examine the determinants of any pharmaceutical expenditure and in a second stage we examine the determinants of pharmaceutical expenditure given that the household has undertaken some expenditure. Finally, to test for the potential existence of sample selection we employed the Heckman correction [START_REF] Heckman | Sample selection bias as a specification error[END_REF].

The determinants of the pharmaceutical consumption

A further question that arises refers to the determinants of access to drugs. Because the access to drugs might depend on previous referral from a GP, we model and estimate a joint process involving the choice of consuming a particular drug and whether or not this arose from a visit to a GP in order to obtain a prescription for it.. Let D* denote the demand for drugs, let V* be the benefits from visiting the physician and let W and K be vectors of explanatory variables for the valuation and participation equations respectively which contain the same explanatory variables as in (3). Then we can write:

i W D + = ' * (5) and i K V + = ' * (6)
We cannot observe both D* and V*, but we can observe D and V taking a value of 1 if there is respectively some drug consumption and whether there is a visit to a GP. Therefore, from ( 5) and ( 6 with zero means, variances equal to 1 and denoting the correlation matrix of the error terms of the two processes underlined in ( 5) and ( 6).

Data and variables

The data

In order to estimate the determinants of the demand for pharmaceuticals, we used data from the 1994 Catalan Health Survey, which is the latest available. This is a general health survey that contains detailed data on pharmaceutical expenditure and use and is representative of the Catalan population All policies mentioned above regarding pricing, reimbursement, and other cost containment measures for pharmaceuticals within Spain, also apply to the case of Catalonia. The survey also contains information on medical utilisation and expenditure and has 15,000 observations in individual and household format. Although the survey does not contain explicitly the co-payment rate for pharmaceuticals, this information has been approximated by two main variables: age (if the individuals is over 65, then the co-payment is zero) and disability (co-payment is reduced to a 10% if individual is disabled). In all other cases, the co-payment should be 40% per prescription item. The mean individual age is approximately 40 and about 3% of the population has some disability, which entitles them to a low co-payment rate. Furthermore, the survey contains information on the individual's family income and education, which provide an indication of the role of socioeconomic position as influencing the demand for drugs. Household size can reveal preferences about lifestyle as well as potential household-specific disease patterns. For identification purposes, we include whether the individual 'smokes' or not to control for potential individual-specific health care need. The same applies to private health insurance entitlement (PHI) which might be an important determinant of access to private health care [START_REF] Vera | Duplicate coverage and the demand for health care in Catalonia[END_REF] and accordingly to the consumption of drugs on an out-of-pocket basis, since PHI does not cover drugs. The survey allows identifying individual self-medication through a set of questions on whether the household has purchased drugs without obtaining a physician prescription that points out the presence of self-medication. Finally, we have included other relevant characteristics such as the pharmacy density and doctor's density in the specific subregions in Catalonia, which is informative on potential access effects on pharmaceutical consumption.

provides come information on whether or not to subsidize certain goods. Out-of-pocket expenditure refers to the declared household pharmaceutical expenditure in the last 30 days and drug use refers to the consumption of drugs in the last 30 days. Health status is measured by a self-reported assessment of health (where 4 refers to excellent health and 1 refers to bad health). We have also included household size for two reasons. First, out-ofpocket pharmaceutical expenditure might reduce total household expenditure. Second, the larger the number of family members the more likely it is that drug consumption may be the result of intra-household health effects of specific illnesses (especially for minor conditions).

Female gender is commonly associated with higher consumption of health care goods and services and male gender is more closely associated with smoking than female gender.

Education influences health related information which, in given the assumptions of [START_REF] Grossman | On the Concept of Health Capital and the Demand for Health[END_REF] is envisaged as increasing the productivity of health production. Disability and age are variables, which are linked to specific cost sharing structures. In our model we have included age squared in order to distinguish between the specific effect of age in general, and that of an advanced age where the individual is likely to be entitled to free prescribed medicines.

Income and private health insurance are variables associated with the individual's capacity to bear the costs of out-of -pocket pharmaceutical expenditure as well as the likelihood of obtaining private prescriptions, which might lead to out-of pocket consumption. Finally, pharmacy density and doctors' density are variables, which are associated with access to drugs.

[TABLE 2 ABOUT HERE]

Results

The results of the econometric approach followed are summarised in Table 3 and are grouped under Model (1) and Model (2). All models were estimated using conventional OLS when estimating expenditure and using probit analysis when the data was dichotomous. running the models, we first tested for selectivity in each of them. We found no evidence of selectivity in Model (1) using the conventional Mills Lambda whereas there is selectivity in Model (2) as the is significantly different from zero and has a positive coefficient (Table 3). The latter indicates that a joint estimation, as employed in this case, is necessary and that a one-equation estimation would produce biased estimates. Furthermore, the difference in the coefficients of drug use [D] would result from heterogeneity since drug use can be the outcome of GP prescribing behaviour. This is a unique feature of pharmaceutical consumption, at least in what concerns prescription medicines, and is very often the consequence of a prior decision to visit a doctor from which a prescription isissued.

Conventional specification tests are reported and indicate acceptable explanatory power and a joint significance for the estimated models.

With regards to the results of Model ( 2), examining those variables that account for the effect of cost sharing we find that although age determines drug use [D] disability does not (Table 2, model ( 2) -left panel. Thus, having a 0% co-payment rate for the retired elderly increases significantly the demand for pharmaceuticals as expected. By contrast, in Model

(1), expenditure [Q] is determined by disability rather than age (Table 3, Model (1) -left panel). This affects results from the fact that the elderly are excluded from co-payments and therefore they undertake very limited out-of-pocket expenditure on pharmaceuticals. In addition, elderly patients have an incentive to contact their GPs and receive prescriptions which can be filled free of charge, and which might otherwise be considered OTC and payable fully out-of-pocket. On the other hand, individuals suffering from some chronic disability may incur expenditure both through filling prescriptions as well as paying out-ofpocket for drugs. When correcting by potential sample selection (Model (2)) for those visiting a GP then age is not significant, suggesting that potential barriers in accessing drugs might be influenced by a previous visit to a GP. Gender does exert some effect on drug consumption.

Males are less likely to use drugs and more likely to consume out-of-pocket than females (Model (1)). However, when we turn into the selectivity corrected in Model (2) we find that males are less likely to visit the GP and accounting for this feature, are more likely to use drugs than females. Again, this result confirms that the potential heterogeneity resulting from GP visits might exert significant influence on the results. Other relevant control variables are household size and health status, both of which are statistically significant and positively associated with drug use and expenditure, and in accordance with the Grossman tradition F o r P e e r R e v i e w [START_REF] Grossman | On the Concept of Health Capital and the Demand for Health[END_REF]. Furthermore, smoking is found to be positively associated with higher out-of-pocket pharmaceutical expenditure and a higher drug use. However, when drug used is corrected by potential visits to the GP we find that smoking was not significant anymore and it turns to be determining a reduced access to the GP.

Possibly one of the most interesting results from the study is the lack of significance of income in predicting out-of-pocket expenditure on drugs while helps predict a significant effect on drug use even when correcting for the estimated parameter by the potential sample selection. This result is in line with Stuart et al (2000) and suggests a small elasticity of demand for drugs. The fact that income explains drug use but not expenditure might suggest that due to the co-payment structure, some individuals might refrain from consuming drugs and might instead consume alternative health care free-of-charge. On the other hand, pharmaceuticals as an input to the health production process are not demanded unless the individual is ill, and thus income plays a small role here once having controlled for health status. Education has some effect on out-of-pocket expenditure suggesting a limited, although potentially important, role of information in drug expenditure. In addition, education is inversely related to the degree of access to the system. This indicates that the lower the education attainment the higher is the access to the GP, most likely to obtain valuable health information.

Finally, two interesting findings point to the importance of access to medicines and the importance of self-medication. Self-medication is estimated as a control variable for outof-pocket health expenditure and displays a positive coefficient as expected.The positive and significant effect of pharmacy density even when accounting for potential sample selection indicates that there is an access motive in the demand for medicines which influences both drug use and out-of pocket expenditures. Finally, those individuals that have private health insurance (PHI) are more likely to report some drug use although that does not significantly influence out-of-pocket expenditure. This could be because private health insurance in Spain provides a faster access to the GP compared with statutory health insurance provided by the NHS. On the other hand, PHI might be correlated with some of the unobserved variables associated with drug access such as income, risk aversion and health information among other determinants.

Discussion

This paper has sought to analyse the determinants of the demand for pharmaceuticals and out-of-pocket expenditures in Catalonia (Spain). Consistently with previous literature, the paper has specifically dealt with individual characteristics of the demand for pharmaceuticals (Stuart, 2000;Poisal et al, 2000). However, in examining the results, one important distinction may be drawn between individual and economic determinants. This distinction is important because although individuals may need to consume specific drugs with or without a prescription, out-of-pocket expenditures may be associated with specific economic determinants (eg. income or having private health insurance). Indeed, consistently with the existing literature, individual characteristics such as ill health and gender appear to be important determinants of the demand for drugs. Empirical evidence from the US suggests that a large proportion of prescriptions for Medicare beneficiaries is associated with individuals reporting several co-morbid illnesses (Stuart et al, 2000). Gender is also a relevant determinant and women were shown to spend more out-of-pocket for drugs than men. This can be partly explained by the prevalence of conditions primarily affecting women after age 55. Age and disability are also important in determining access to drugs and in explaining out-of-pocket pharmaceutical expenditure. Our evidence suggests that due to the prevailing cost-sharing structure in Spain and Catalonia variables such as age and disability might have different effects on pharmaceutical expenditure and use compared with other studies. As expected from the prevailing cost sharing structure in Catalonia, age appears to be a significant determinant of drug access but not of out-of-pocket expenditure while disability is the other way around. The literature also identifies disability at young age as a relevant determinant of pharmaceutical expenditure. Poisal et al (2000) find that disabled beneficiaries under the age of 65 spend almost twice as much as those over the age of 65. However, the relevance of age is not entirely clear in that although age and health status are associated with expenditure, personal drug costs for chronically ill patients appear to be lower than for other age groups due to cost sharing exemptions (Stuart, 2000). [START_REF] Brendt | Prescription drug process for the elderly[END_REF] show that there is no clear evidence of the direction of age-related effects and, if they exist, they really depend on the type of drug analysed and whether it treats chronic or age-related conditions or not. Thus, a distinction may be set between medicines that are subsidized by the NHS and those that are not. When drugs are not rationed or co-payments are small we may expect pharmaceutical expenditure to rise. However, when estimating the effect of cost sharing on demand, we should take into account that co-payments are set according to individual characteristics that result from higher need of pharmaceutical consumption due to a fragile health status.

Turning to the economic determinants of drug expenditure and use, private health insurance coverage together with income provides some evidence of a higher likelihood of drug use among the most affluent consumers, although both variables were not significant predictors of out-of pocket expenditures. This results from the fact that OTCs are normally low priced drugs whereas the co-payment that less affluent individuals might have to pay for drugs is significant. On the other hand, this results from the fact that the cost sharing structure in Spain is based on age rather than on income, and the elderly, who do not pay for drugs, often is more affluent than households or individuals of younger average age. Finally, both income and PHI appear to be strong determinants of drug use, which implies that there might be socio -socio-economic barrier to the access for drugs (once controlling for health status).

The current cost sharing structures (40% of the cost of medicines if the full rate applies) or the cost of obtaining medicines on an out-of-pocket basis may deter consumers from accessing drugs in certain circumstances.

Recent work on the influence of insurance on the demand for prescription drugs finds that private insurance coverage leads to increased demand for drugs [START_REF] Coulson | Estimating the moral hazard effect of supplemental medical insurance in the demand for prescription drugs by the elderly[END_REF].

Interestingly, the influence of income remains once correcting for sample selection to account for the physician influence on prescribing and dispensing. Physicians, as agents acting on behalf of patients, are key in determining demand for medicines through their clinical practice and prescribing behaviour. The significance of self-medication in increasing pharmaceutical out-of-pocket expenditure indicates that a part of the population might not consume drugs on the basis of doctor's prescription but based on their own perceptions and available health information. Finally, once controlling for the influence of self-medication we find that improved access to pharmacies increases both drug use and out-of-pocket expenditure.

In examining drug use, we find that results change significantly when drug use is jointly estimated with the access to GPs, indicating that the model has captured part of the unobserved heterogeneity resulting from the potential drug use with without a prescription.

Furthermore, the decision to demand drugs available only on prescription is taken by the physician rather than the patient. In Catalonia GPs act as gatekeepers and all prescriptions covered by the NHS originate from them or from specialists (López and Mossialos, 2000).

Therefore, the decision to consume prescribed pharmaceuticals cannot be separated from the decision to consume health care since the latter is in part the expected result of visiting a (Vera-Hernandez, 1999) suggests that whereas people that purchase PHI tend to visit specialists more often, this is not the case with GP visits, typically prescribing drugs subsidised by the NHS.

This paper also shows that income does not influence out-of-pocket expenditure but other variables, such as access to pharmacies; self-medication and household size have a significant influence over such expenditure. On the other hand though, income does influence drug use; this finding indicates that certain cost-sharing structures, which are not associated with individual income might have an impact on access to medicines. Whereas higher income and education were associated at individual level with a higher demand for pharmaceuticals, neither determines out-of-pocket expenditure at family level. As the utility of medicines is zero if the individual is not ill, our finding implies that medicines consumed by individuals when ill, are independent of income and education, even though more educated and wealthier individuals are more likely to demand and consume them.Education may also be a proxy for an individual's ability to act in order to prevent illness rather than underline individual demand for a health related input.

Finally, this paper shows the difficulties that may appear when using general health surveys based on individual data in estimating the demand for pharmaceuticals. Our results suggest that estimating the demand for pharmaceuticals with survey data is complex for many reasons. Available surveys just show the amount of pharmaceutical expenditure that the individual (or the family) has undertaken. However, pharmaceutical expenditure includes outof-pocket expenditure (for OTC products and, potentially, prescription-only medicines available on a private prescription, or, simply, available at the pharmacy without a prescription), and co-payments (most notably for publicly covered prescription medicines); the indivisibility between the two types of out-of-pocket expenditure limits empirical research. In this study we estimated that 13% of the Catalan population has consumed a drug without any prescription, from where a half of them were drugs for illnesses that would require a prescription. As a result, more work should be undertaken in improving available databases to test hypotheses on the individual demand for pharmaceuticals. This paper is also a first attempt to account for a reduced form of an individual demand where the role of copayments is determined indirectly. Although the two-part model employed accounts for a possible two-stage decision making-process, it is likely that other health related characteristics and more complex models would provide us with more accurate results.

Empirical problems emerge when using health surveys that contain information on health expenditure. Unobserved patient heterogeneity may be significant due to the heterogeneity of Consequently, a censuring problem appears when estimating the demand for pharmaceuticals.

When examining individual data on pharmaceutical expenditure we may encounter zero observations that may be due to different reasons. First, there may be an infrequency problem when using data from only one year. Second, healthy individuals do not consume pharmaceuticals as its unnecessary for them. Third, as previously noted, elderly individuals may be ill and most likely consume pharmaceuticals, but pay nothing for pharmaceutical consumption because of their health insurance coverage, therefore, zero expenditure arises.

Fourth, even though some people should consume pharmaceuticals, it may be the case that some may not be able to afford the high co-payments for some drugs (due to the high prices for the latter), however this is less likely (corner solution) to happen due to the increased possibility of consuming a substitute drug (generic).

Conclusions

Examining the determinants of the demand for pharmaceuticals and of out-of-pocket expenditures is key in understanding the potential impact of changes in drug regulation in a country. In particular, this paper has found that out-of-pocket expenditure on pharmaceuticals in the Spanish Autonomous Region of Catalonia is sensitive to the effect of the statutory copayment, but is also influenced by individual patterns of self-medication and geographical access to drugs. On the other hand, drug use is determined by income, private health insurance, the statutory co-payment and health status. From a methodological perspective we have found that the demand for pharmaceuticals could be affected by previous consultation with a general practitioner.

Our research has several policy implications both for Spain and other jurisdictions.

First, we confirm that self-medication explains a remarkable share of out-of-pocket expenditure. Therefore, the regulation of the market for OTC products should bear in mind this feature. Deregulation of pricing and competition in the OTC market, should enable consumers to obtain better deals on their medications. Second, the importance of income and private health insurance in determining drug use suggests that there might be a socio-

  prescription, where the consumer bears the entire cost out-of-pocket.

A

  special Commission on rational drug use determines reimbursement policy where the 17 autonomous regions as well as the pharmaceutical industry, consumers, trade unions, professional associations and experts designated by the Ministry of Health are present. The objective of this Commission is to consider drugs for inclusion into the reimbursement (positive) list. The general criteria for inclusion are: a) the characteristics of the disease, b) the inclusion of inpatient groups, c) the drug's therapeutic benefit, d) public expenditure limitations, and e) the existence of therapeutic alternatives. OTCs are excluded from reimbursement, unless prescribed by a physician. 68% of prescribed drugs are subject to copayments.

  into account prescribing expenditure. Financial incentives were introduced in Navarre (1998) and in

  consumption patterns than non-retirees. Whilst expenditure per active individual was below €60 in 2000, expenditure per pensioner in 2003 amounted to €140 (Costa-Font andPuig- Junoy, 2004).

  pharmaceuticals (and thus the individual -specific cost-sharing characteristics)

  Given (3), demand analysis under price heterogeneity 4 leads to examining out-oflogs, the set of determinants (such as cost-sharing characteristics [p], changes in income [y], health status [h], as well as other specific characteristics[z]

  ) we can write the bivariate normal distribution as BivN ዊp

  Model (1), reports the results of the two-part model for the determinants of out-of-pocket pharmaceutical expenditure [Q] and pharmaceutical use [D]. Model (2) contains a Heckman selection model examining the determinants of drug use [D] accounting for the likely effects physician (GP) and obtaining a prescription [V]. Before proceeding with

  Table 2 contains the description of the variables employed in the study. We separate the dependent variables (out-of-pocket expenditure [Q], drug use [D] and GP visits [V]) from the explanatory variables (household size, gender, age, disability, education, smoking, private health insurance, self-medication, doctor density in region and pharmacy density in region).

  Information on prices for all medicines is not always available easily and when it is, it is surrounded by controversy. Being in a position to know with precision cost-sharing policies affecting different segments of the population, has enabled this research to instrument the price effect by using age and disability information.

	pharmaceuticals as consumer products.
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Table 1 . Number of prescriptions, expenditure, share of retired consumers and effective co-payments in Spain, 1986-2002

 1 economic vector explaining the access to drugs. Indeed, because co-payments in Spain are not associated with individual's income, but depend on age and disability, there may be access to medicines, such that poorer patients who do not meet age and disability eligibility criteria, may still be having to pay 40% of the cost of their medicines. To date there is still no study examining inequalities in accessing medicines in Spain and therefore future research further investigate this issue. However, in light of the evidence presented in this paper, it would be sensible to introduce a reform of cost-sharing to include means-tested (income-based) co-payments. Finally, the effect of pharmacy density in explaining drug use indicates that the increasing density of pharmacies in Spain might not be neutral in influencing the demand for drugs. Therefore, some additional emphasis should be placed in controlling pharmacy growth, with stricter criteria for new pharmacies to open.

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Note: * Cost-sharing expenditure divided by total expenditure Source: Consejo del Colegio de Farmaceuticos, 2003. Page 23 of 25 Editorial Office, Dept of Economics, Warwick University, Coventry CV4 7AL, UK

Table 3 . The demand for pharmaceuticals and pharmaceutical expenditure: results from the Catalan Health Survey (1994) of a two-part model of pharmaceutical expenditure and pharmaceutical use [Model (1)] and a two-part model of pharmaceutical use and physician visit [Model (2)]

 3

					Model (1)			Model (2)
	Variables			Pharmaceutical expenditure (Q)	Pharmaceutical use (D)	Pharmaceutical use (D)	Physician visit (V)
				Coeff	S.E.	Coeff	S.E.	Coeff	S.E.	Coeff.	S.E.
	Nmemfam			0.089*	(0.039)	0.125* (0.011) 0.082* (0.017) -0.007 (0.011)
	Sex			0.1428*	(0.041)	-0.094* (0.027) 0.056* (0.041) -0.136* (0.028)
	Incap Age Age 2			0.346* -1.9x10 -4 1.34x10 -4	(0.117) (4.6x10 -4 ) 0.006* (0.002) -0.006* (0.004) 0.002* (0.001) 0.011 (0.082) -0.033 (0.096) 0.159* (0.082) (1.1x10 -4 ) 1.9x10 4 * (3x10 -5 ) 1.9x10 -4 * (5x10 -4 ) 4.18x10 -4 (3.2x10 -4 )
	Lincome			0.031	(0.083)	0.253* (0.024) 0.192* (0.040) -0.014 (0.025)
	Educ1			0.027	(0.068)	-0.093 (0.059) -0.282 (0.102) 0.333* (0.061)
	Educ2 Educ3			-0.150* -0.025	(0.054) (0.061)	-0.072 (0.050) -0.144 (0.093) 0.111* (0.053) -9x10 -4 (0.059) -0.146 (0.106) 0.109* (0.061)
	Smoke			0.089*	(0.045)	-0.071* (0.034) 0.034 (0.025) -0.124* (0.036)
	Phi			0.973	(2.357)	0.124* (0.005) 0.135* (0.051)	-	-
	Health			-	-	0.152* (0.012) 0.137* (0.012) 0.281* (0.013)
	Self			0.033*	(0.011)	-	-	-	-	-	-
	Phar_des			0.230*	(0.065)	0.627* (0.166) 0.594* (0.168) 0.987	(0.678)
	Doctor_dens		-1.39	(1.310)	2.534 (1.683) -2.045 (1.678)	0.40	(0.467)
	Intercept			7.30*	(1.580)	-3.253* (0.369) -0.870 (0.619) 0.79*	(0.345)
										0.69	0.023
				-0.583	0.637
	Wald ( ) 2 R 2 Pseudo-R 2 LR a (All =	0	)	1238.5 0.25		0.23 1199.55				394.98
	Log-Likelihood	-4567.9						-6530.24
	LR a ( =0)									3.89

The information system to be developed in the near future for a national prescription monitoring systemthrough the so-called Independent Prescription Identification Terminal -might be used to identify and warn physicians who are judged to be overprescribing.

Examining elasticities is important because I might be informative on the effects of subsidies on drugs. Indeed, subsidising more those commodities whose consumption tends to fall with income. Thus, income elasticity

Editorial Office, Dept of Economics, Warwick University, Coventry CV4 7AL, UKSubmitted Manuscript

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