The traditional economic theory suggests that changes in the money supply or in the interest rates can influence the business cycle, but not the long-run potential output. In other words, monetary policy is neutral over the long-run. In this paper we use some new developments in econometrics to test for the existence of a long-run relationship between the monetary policy instrument used by most Central Banks - short-term interest rates - and real output. Using annual data for 14 emerging and developed countries our results offer overall support for the traditional economic theory.Money neutrality, monetary policy, cointegration tests.

Reginaldo Pinto Nogueira

English

Research Papers in Economics

     
 
 
  
  
Volume 29, Issue 3 
  
Is monetary policy really neutral in the long-run? Evidence for some emerging 
and developed economies 
  
 
 
Reginaldo Pinto Nogueira Jr. 
Fundação João Pinheiro, Brazil 
Abstract 
The traditional economic theory suggests that changes in the money supply or in the interest rates can influence the 
business cycle, but not the long-run potential output. In other words, monetary policy is neutral over the long-run. In 
this paper we use some new developments in econometrics to test for the existence of a long-run relationship between 
the monetary policy instrument used by most Central Banks - short-term interest rates - and real output. Using annual 
data for 14 emerging and developed countries our results offer overall support for the traditional economic theory.
The author would like to thank, without implicating, an anonymous referee for valuable comments on the paper. 
Citation: Reginaldo Pinto Nogueira Jr., (2009) ''Is monetary policy really neutral in the long-run? Evidence for some emerging and developed 
economies'', Economics Bulletin, Vol. 29 no.3 pp. 2432-2437. 
Submitted: Jun 13 2009.   Published: September 28, 2009. 
 
       1
1.  Introduction 
The traditional economic theory suggests that monetary policy can influence the business 
cycle, but not the long-run potential output. In other words, monetary policy is neutral over 
the  long-run.  Evidence  on  this  matter  can  be  found  in  several  studies,  such  as  Olekalns 
(1996), Sarletis and Koustas (1998), Bernanke and Mihov (1998), Bullard (1999) and Bae, 
Jensen and Murdock (2005). However, this literature faces two central challenges. Firstly, 
most studies have only analyzed developed countries
1. This evidence may not be relevant for 
emerging countries, since nominal and real interest rates in developed countries are generally 
much lower and less volatile than in the emerging world (see for e.g. Calvo and Reinhart, 
2002; Ferreira and León-Ledesma, 2007). Secondly, much of the empirical investigation has 
focused on the neutrality of monetary aggregates, whereas Central Banks have been widely 
employing short-term interest rates as their main policy instrument
2. Therefore, this evidence 
can  be  seen  more  as  favoring  aggregates  neutrality  than  monetary  policy  neutrality.  An 
important exception is Aksoy and León-Ledesma (2005), who check the long-run neutrality 
of short-term interest rates using data for the U.S and the U.K.  
In this sense, in this paper we ask whether the monetary policy, through the setting of 
short-term nominal interest rates, affects long-run output in a sample of 14 developed and 
emerging countries. As in Aksoy and León-Ledesma (2005), we apply the cointegration test 
developed by Pesaran, Shin and Smith (2001) in order to overcome the problem of different 
orders of integration of the variables. Our results provide overall support for the traditional 
economic theory, as we were able to reject the null hypothesis of no long-run relationship 
between real output and nominal interest rates for only one out of the 14 countries analyzed. 
The rest of the paper is as follows: section 2 presents the data and applies some unit 
root tests; section 3 investigates the existence of long-run relationships; section 4 concludes. 
 
2.  Data and unit root tests 
We collected annual data on real output and short-term nominal interest rates for a sample of 
14 emerging and developed countries. Data on Brazil’s real output was obtained from IPEA 
(http://www.ipeadata.gov.br); all the other data was obtained from the IMF’s IFS database. 
 
Table 1: Sample periods and data definitions  
                                                 
1 Relevant exceptions include Moosa (1997), Bae and Ratti (2000), and Starr (2005). 
2 Both monetary aggregates and interest rates are expected to have useful information to explain business cycles. 
However, several studies have argued that since the end of the 1970s the relationship between aggregates and 
fundamentals collapsed (see Clarida, Gali and Gertler, 2000). A common response to this information loss by 
many of the countries considered in this paper have been the adoption of explicit or implicit inflation goals, with 
the utilization of short-term interest rates as operating targets, normally through the use of Taylor-type rules. 
Country  Sample Period  Interest rate  Real output 
U.S.  1948-2007  Treasury bill rate  GDP vol. (2000=100) 
U.K.  1948-2007  Treasury bill rate  GDP vol. (2000=100) 
Sweden  1950-2007  Bank rate   GDP vol. (2000=100) 
Switzerland  1948-2007  Discount rate  GDP vol. (2000=100) 
Canada  1948-2007  Treasury bill rate  GDP vol. (2000=100) 
Japan  1955-2007  Discount rate  GDP vol. (2000=100) 
New Zealand  1954-2007  Discount rate  GDP vol. (2000=100) 
Brazil  1948-2007  Money market rate  GDP (2007 prices) 
Colombia  1968-2007  Discount rate  GDP vol. (2000=100) 
Peru  1950-2007  Discount rate  GDP vol. (2000=100) 
India  1963-2007  Bank rate   GDP vol. (2000=100) 
South Korea  1953-2007  Discount rate  GDP vol. (2000=100) 
Venezuela  1957-2007  Discount rate  GDP vol. (2000=100) 
South Africa  1950-2006  Treasury bill rate  GDP vol. (2000=100)   2
We applied some ADF and DF-GLS unit root tests on the data collected. The results are 
reported in Tables 2 and 3. If a series is I(0) the tests should reject the null of a unit root. 
Taken as a whole, the results support the hypothesis of non-stationarity in real output, but 
provide mixed evidence regarding interest rates (in fact, we can reject the null for only 5 
countries). This finding brings a disturbing issue at the theoretical point of view, which is a 
possible unit root in interest rates. The reason for that, as discussed by Aksoy and León-
Ledesma (2005), is that according to the traditional economic theory interest rates should be 
stationary for a dynamic general equilibrium to exist
3.  
 
Table 2: Unit root tests on log of real output 
 
 
Table 3: Unit root tests on nominal interest rates 
 
                                                 
3 Other studies have also raised the issue of non-stationarity in interest rates (see for e.g. Rapach and Weber, 
2001). This result may be due to the well-known low power of unit root tests (for a discussion, see Ferreira and 
León-Ledesma, 2007).  
  Lags  ADF  ADF +  DF-GLS  DF-GLS + 
U.S.  0  -1.398  -2.271  3.608  -1.894 
U.K.  2  -0.193  -2.169  1.616  -2.033 
Sweden  2  -2.078  -2.089  0.673  -1.281 
Switzerland  2    -2.799*  -1.776  0.859  -0.911 
Canada  2  -1.969  -1.852  1.532  -0.999 
Japan  0     -6.489**  -1.302  1.327  -0.086 
New Zealand  0  -1.033  -2.142  3.224  -1.654 
Brazil  2  -1.913  -1.234  0.380  -1.211 
Colombia  1  -0.872  -2.766  0.885  -2.128 
Peru  2  -1.348  -2.051  1.186  -1.401 
India  4    4.517    0.347  0.883  -0.222 
South Korea  0  -0.378  -1.119  3.595  -1.091 
Venezuela  1  -1.736  -2.550  0.665  -1.828 
South Africa  1  -1.923  -1.792  0.903  -1.153 
Notes: The numbers are the test statistics of the ADF and DF-GLS unit root tests under the null hypothesis of 
non-stationarity. Number of lags determined using Akaike Info Criteria. + indicates a trend was included in 
the test’s equation. * indicates rejection of the null at the 10% significance level. ** indicates rejection of the 
null at the 5% significance level. 
  Lags  ADF  ADF +  DF-GLS  DF-GLS + 
U.S.  2  -2.051  -1.834  -1.442  -1.724 
U.K.  2  -2.107  -1.659  -1.125  -1.417 
Sweden  0  -2.148  -2.090    -1.876*  -2.005 
Switzerland  0  -2.250  -2.502      -2.345**  -2.478 
Canada  0  -2.079  -1.858  -1.501  -1.781 
Japan  1  -1.567      -4.075**  -1.160      -3.965** 
New Zealand  0  -2.341  -2.250  -1.895  -2.152 
Brazil  0      -4.933**      -5.011**     -4.900**      -5.091** 
Colombia  0  -1.632  -1.384  -1.317  -1.316 
Peru  3      -3.199**     -3.228*      -3.121**      -3.297** 
India  2  -1.445  -1.035  -1.143  -1.202 
South Korea  0  -1.535  -2.261  -1.536  -1.902 
Venezuela  0  -1.656  -2.299  -1.375  -2.358 
South Africa  4  -1.454  -0.548  -0.674  -1.178 
Notes: The numbers are the test statistics of the ADF and DF-GLS unit root tests under the null hypothesis of 
non-stationarity. Number of lags determined using Akaike Info Criteria. + indicates a trend in the test’s 
equation. * indicates rejection of the null at the 10% significance level. ** indicates rejection of the null at 
the 5% significance level.   3
The results of our unit root tests bring some complications to our investigation. Traditionally, 
studies on the long-run monetary policy neutrality are based on coitegration tests. When the 
hypotheses of non-stationarity of all the variables are not rejected it is easy to justify the use 
of conventional cointegration tests, such as those proposed by Johansen. However, our unit 
root tests show that if on the one hand there is strong evidence favoring non-stationarity in 
real output, we are not sure about the integration order of nominal interest rates. For some 
countries it seems to be I(1), and for others it seems to be I(0). Furthermore, as discussed 
before an additional complication is that economic theory predicts that interest rates should be 
stationary.  In  this  sense,  we  follow  Aksoy  and  León-Ledesma  (2005)  and  apply  the 
cointegration test developed by Pesaran, Shin and Smith (2001), which does not require any a 
priori  conclusion  with  respect  to  the  integration  order  of  the  variables.  In  our  case,  the 
importance of this test is that by applying it we are not required to make any assumption 
regarding the stationarity of interest rates. Since our results for this variable provided mixed 
evidence, it is reassuring to know that our results are not dependent on ad hoc assumptions. 
Moreover, we can stick with the traditional economic theory, that states that interest rates 
should be stationary, but at the same time test for long-run relations with sound econometrics. 
 
3. Testing for long-run level relationships 
Pesaran,  Shin  and  Smith’s  (2001)  approach,  as  described  by  Aksoy  and  Leon-Ledesma 
(2005), is based on the estimation of an unconstrained dynamic error correction representation 
for  the  difference  of  the  variables  involved,  and  testing  whether the  lagged  levels  of  the 
variables  are  significant
4.  In  other  words  the  test  consists  of  estimating  the  following 
autoregressive distributed-lag (ARDL) model: 
 
1 1 2 1
1 1
m m
t o t t k t k k t k t t
k k
y y i y i i β β β ϕ φ ϑ η − − − −
= =
∆ = + + + ∆ + ∆ + ∆ + ∑ ∑             (1) 
 
Where ∆y represents the first difference of the log of real output, and ∆i the first difference of 
nominal interest rates. Unlike Aksoy and León-Ledesma (2005) we use the first difference of 
interest  rates  in  equation  (1),  whereas  they  use  the  percentage  change  of  interest  rates. 
Although  it  is  mainly  a  matter  of  how  to  interpret  the  coefficients,  under  different 
transformations, our approach is more commonly used in the literature.   
In order to test for the existence of a long-run relationship between real output and 
nominal interest rates, we apply an F-test of joint significance of the lagged levels of the 
variables. If the F-statistic for the joint null of zero coefficients shows to be insignificant, then 
it cannot be reject the null hypothesis that the variables are not related in the long-run. The 
procedure is based on a bounds test, in which the lower-bound represents the critical value if 
all the variables were I(0), and the upper-bound represents the critical value if all the variables 
were I(1)
5.  
We follow the procedure suggested by Pesaran, Shin and Smith (2001), and do not 
reject the null if the F-statistic is lower than lower-bound of the critical value. On the other 
hand, the null hypothesis is rejected in favor of the alternative if the F-statistic exceeds the 
upper-bound of the critical value. When the F-statistic lies between the bounds, then the result 
is inconclusive. 
                                                 
4 For a technical discussion on the test, the reader is referred to Pesaran, Shin and Smith (2001). Interesting 
applications of this methodology can be seen in Vita and Abbot (2002), Atkins and Coe (2002) and Narayan and 
Narayan (2005). 
5 The critical values for different specifications can be found in Pesaran, Shin and Smith (2001). We use two 
specifications, which represent cases III and IV in Pesaran, Shin and Smith (2001). In the first one only a 
constant is included in equation (1), whereas in the second one a constant and a trend are included.   4
 
3.1 Results 
The results are reported in Table 4
6. We considered two possibilities for the long-run level 
relationship between the variables: one with an unrestricted constant (case III in Pesaran, Shin 
and Smith, 2001), and another with an unrestricted constant and an unrestricted trend (case IV 
in Pesaran, Shin and Smith, 2001).  
 
Table 4: Bounds testing for long-run level relationships  
 
First of all, the results found reinforce Aksoy and León-Ledesma’s (2005) findings, as we too 
were able to reject a long-run relationship between the variables for the U.K. and the U.S. 
Furthermore,  this  result  seems  to  apply  also  for  other  developed  countries  and,  most 
importantly, for our sample of emerging countries as well. Only for Peru the null of no long-
run  relationship  was  rejected  in  both  specifications,  whereas  in  the  cases  of  Swtizerland, 
Japan and South Africa the second specification, which includes an unrestricted trend in the 
equation, does provide support of long-run monetary policy neutrality. For Canada and India 
the results are inconclusive in the first specification, as the F-statistic lies between the bounds, 
but clearly favor long-run monetary neutrality in the second specification. Finally, in the case 
of Brazil the results do not seem to depend on the inclusion of the hyperinflation data (1988-
1994), supporting long-run monetary neutrality with both specifications for both samples.  
In  summary,  the  results  found  provide  overall  support  to  the  traditional  economic 
theory,  suggesting  that  monetary  policy  and  real  output  do  not  have  a  long-run  level 
relationship, i.e. are not cointegrated. 
 
4. Conclusion 
The traditional economic theory suggests that monetary policy can influence the business 
cycle, but not the long-run potential output. In this paper we have investigated this hypothesis 
for a sample of 14 emerging and developed countries, checking whether there is a long-run 
                                                 
6 For Brazil we also applied tests for a sample that excludes the hyperinflation period (1988-1994), which is 
characterized by very high and volatile nominal interest rates.  
  F-stat  Lower 
Bound 
Upper 
Bound 
F-stat +  Lower 
Bound 
Upper 
Bound 
U.S.  2.884  4.490  5.730  5.520  6.560  7.300 
U.K.  1.705  4.490  5.730  2.542  6.560  7.300 
Sweden  2.853  4.490  5.730  2.831  6.560  7.300 
Switzerland  8.504  4.490  5.730  3.814  6.560  7.300 
Canada  5.407  4.490  5.730  3.733  6.560  7.300 
Japan  9.517  4.490  5.730  1.087  6.560  7.300 
New Zealand  0.986  4.490  5.730  3.336  6.560  7.300 
Brazil  4.169  4.490  5.730  1.961  6.560  7.300 
Brazil*  1.558  4.490  5.730  0.778  6.560  7.300 
Colombia  2.069  4.490  5.730  4.432  6.560  7.300 
Peru  7.299  4.490  5.730  8.743  6.560  7.300 
India  4.937  4.490  5.730  1.312  6.560  7.300 
South Korea  1.933  4.490  5.730  2.343  6.560  7.300 
Venezuela  1.424  4.490  5.730  3.038  6.560  7.300 
South Africa  6.424  4.490  5.730  5.511  6.560  7.300 
Notes: Bold numbers indicate rejection of the null of no long-run relations. + indicates the inclusion of an 
unrestricted trend in the test’s equation; otherwise only a constant was included. Brazil* refers to the results 
obtained excluding the hyperinflation period (1988-1994). Critical values were obtained from Pesaran, Shin and 
Smith (2001) in tables Ciii and Civ.    5
relationship between real output and the monetary policy instrument used by most Central 
Banks - short-term nominal interest rates.  
  Given differences in integration orders of the variables, we followed Aksoy and León-
Ledesma  (2005)  and  applied  the  bounds  testing  approach  to  coitegration,  developed  by 
Pesaran, Shin and Smith (2001). This procedure allows investigating the existence of long-run 
relationships irrespective of the integration order of the variables.  
  In general, the results give support to the traditional economic theory, as we were able 
to reject the null of no long-run relationships only for one out of 14 countries. In other words, 
monetary policy does not seem to affect output in the long run.  
 
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Is monetary policy really neutral in the long-run? Evidence for some emerging and developed economies

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Is monetary policy really neutral in the long-run? Evidence for some emerging and developed economies

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