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Impact of Monetary Policy on Agricultural Food Prices




  •  

    “Impact of Monetary Policy on Agricultural Food Prices:

    A Case of Pakistan

    By

     Muhammad Rizwan Altaf

    &

                                         Muhammad Najaf Ali Maswan 

     

     

    Introduction

    “Monetary policy is the process by which the monetary authority of a country controls the supply of money, often targeting a rate of interest for the purpose of promoting economic growth and stability.”

    There are two types of monetary policy i.e. expantionary(loose) monetary policy and contractionary(tight) moentary policy, where an expansionary policy increases the total supply of money in the economy more rapidly than usual, and contractionary policy expands the money supply more slowly than usual or even shrinks it. With the help of monetary policy the government and the central bank controls money supply, interest rate, availability of money to help the economy steer towards prosperity. The government and the central bank control the monetary policy using various types of tools like monetary base, reserve requirements, interest rate, discount lending, etc.

    Rising food prices pose a serious challenge to monetary policy especially for middle income and low income countries. On the one hand tightening monetary policy would be ineffective in the face of an exogenous shock to relative prices—which may be behind recent food price inflation. Moreover, tightening monetary policy could choke the agricultural supply response and dampen growth in countries experiencing a slowdown at the same time that food and energy prices are high. On the other hand loosening monetary policy, driven by the need to manage capital inflows and real exchange rate appreciations, would exacerbate the situation.

    According to World Bank’s report on Latin America and Caribbean region food price inflation has a detrimental impact on the income, nutrition, and health of poor consumers. The report furthur says that Even if a country is a net seller of food, most people are net buyers and negatively affected by rising food prices. Poor people are disproportionately affected because they spend a larger share of their income on food. Rising food prices thus reduce the real income of the most vulnerable people, with serious nutritional and health consequences.[2]

    According to Food and Agriculture Organization of United Nations (FAO), by mid-2008, international food prices had skyrocketed to their highest level in 30 years. This, coupled with the global economic downturn, pushed millions more people into poverty and hunger. In December 2010, the FAO food price index rose above its 2008 peak. The index dropped to an 11-month low in October 2011, but food prices still remained generally higher than previous year and very volatile. [3]

    Previous researches show that monetary policy does has an impact on the agricultural food prices like Khundrakpan & Das say that it is theoretically argued that, as agricultural food prices are more flexible they respond faster to change in money supply than non-agricultural prices, which are relatively inflexible. Thus, agriculture prices are characterized by short-term contracts and respond more quickly to monetary changes than the prices of other goods (2011). That is why it is necessary to look into fact how monetary policy impacts the agricultural food prices. That is why Kargbo says that agricultural and macroeconomic policy makers should cooperate more closely in designing economic reforms policies (2005).

    Problem Statement

    It is important for the policy makers to make credible announcemets because the decisions of the private agents (in this case Farmers) are resting on the announcements. If private agents believe that policymakers are committed to lowering inflation, they will anticipate future prices to be lower than otherwise. If a policymaker’s announcements regarding monetary policy are not credible, policy will not have the desired effect.

    The high volatility of food prices is a concern to the general public and policy makers because such price movements are a deterrent to increased agricultural productivity and tend to intensify inflationary pressures. Food price volatility increases the uncertainty faced by farmers and the agricultural sector. In particular, price volatility affects farmer’s investment decisions, which has serious ramifications for the growing farm debt, farm incomes and productivity.

     

     

    Literature Review

    Das (2011) studied the impact of monetary policy on food prices in India from the time period of 2001 to 2010. They studied the relative response of food and manufactured products prices to change in interest rate and money supply both of which are tools for the monetary policy, but our study is limited to the food prices only. The authors have mentioned the variables involved clearly. They have used vector error correction model (VECM). They have also considered “Call Rate” which is also beyond the boundaries of our study. The authors have considered long-run and short-run scenario for the comparision. They conclude that in the long-run, money supply leads to rise in the prices of food. The impact of money supply is, however, more on food prices than on manufactured prices. There is no evidence of long-run neutrality of money, as increase in money supply leads to less than proportionate change in price. In the short-run, there is overshooting in the prices of both food and manufactured products from their respective long-run equilibrium following monetary shocks. The overshooting, however, is more in food prices than in manufactured prices. But money supply increases with rise in food prices and decreases with the rise in manufactured prices.

     

    Like Khundrakpam & Das, Frankel (2006) also studies the effect of monetary policy on real commodity prices. But unlike Khundrakpam & Das, Frankel looks at connections between monetary policy, and agricultural and mineral commodities instead of food and manufactured prices. Frankel’s main focus for monetary influences is United States and compares it with smaller countries like Mexico, Indonesia, Brazil, etc. He claims that low real interest rates lead to high real commodity prices. Frankel uses the theory from an analogy with Dornbusch’s exchange rate overshooting. He says that the deep reason for the overshooting phenomenon is that prices for agricultural and mineral products adjust rapidly, while most other prices adjust slowly. The relationship between real interest rates and real commodity prices is also supported empirically. One channel through which this effect is accomplished is a negative effect of interest rates on the desire to carry commodity inventories. The paper concludes with a consideration of implications for monetary policy.

     

    Another study carried out is by Kargbo (2005), who studies the impacts of monetary policy and macroeconomic factors on food prices in four West African countries. He talks about the volatility of food prices and declares it a concern for general public and policy makers because they are deterrent to increased agricultural productivity and tend to intensify inflationary pressures. He studies the impact of structural and macroeconomic programmes for the period of two decades. His theroy makes a case for rising food prices by explaning it from two prespectives i.e. Structuralists and monetarists. Like Khundrakpam & Das, Kargbo also uses Vector Error Correction Model. He concludes that food African countries have been facing significant increase in food prices which is not good because food accounts for up to 73 percent of household budgets in some African countries, food price increases have severe political implications because people buy food more frequently than any other item in the CPI. The empirical results show that shocks to money supply, exchange rates and trade policies have significant impacts on food prices, real incomes and per capita domestic food production. Moreover, results show strong feedbacks amongst the variables, and rapid adjustment towards long-run equilibrium levels after shocks in the system. The policies adopted after the proper study can influence consumption patterns, and have serious implications for poverty reduction, food security issues and agricultural growth in Africa.

     

    The study is beyond our area of interest because it also considers the policy implementation whereas our study is limited to the impact of montary policy on agricultural food prices.

    Abdullah & Kalim (2012) did an empirical analysis of food price inflation in Pakistan.  This study focuses on the identification of main determinants of food price inflation in Pakistan. Using the data from 1972 to 2008, Johansen’s co-integration technique is utilized to find out the long run relationships among food price inflation and its determinants like inflation expectations, money supply, per capita GDP, support prices, food imports and food exports. They used Vector Error Correction Model (VECM) to find out the short run Dynamics. The error correction term of our short run model is also statistically significant with a negative sign. Findings of the study showed that ‘inflation expectations’ had dominant role in determining food price inflation both in long run and short run in Pakistan. Empirical results of this study prove that money supply or expansionary monetary policy does not affect food price inflation significantly in Pakistan. In this situation it is suggested that government should encourage the expansion in private sector credit especially towards the agricultural and its related sectors. Increase in public expenditures on the provision of infrastructure for rural areas will also be helpful for utilization of the potential of agriculture sector.

    Research Objectives

    Ø  To show a relationship between monetary policy and agricultural food prices

    Ø  How the monetary policy impacts agricultural food prices

    Ø  To look at the monetary instruments available to control inflation in agricultural sector.

    Variables

    Ø  Monetary Policy (Independent Variable)

    Ø  Agricultural Food Prices (Dependent Variable)

    Hypothesis

    Following are the hypothesis that is intended to be tested in this paper.

    H0 Monetary Policy has an impact on Agricultural Food Prices of Pakistan

    H1 Monetary Policy does not has an impact on Agricultural Food Prices of Pakistan

    Methodology

    For the estimation of the effects of the stated variables on the agricultural food prices, “Vector Error Correction Model (VECM)” is called for the determination.

    Limitations

    The limitations we faced were mainly related to availability of data. We tried multiple sources for data collection like State Bank of Pakistan, Economic Surveys of Pakistan, World Bank, etc. We were able to achieve data for only 12 years i.e. from FY2000-FY2012. This restricted our study to Johansen’s cointegration test only and we were unable to perform VECM. Also, we had to drop M1 and M2 from the model because we could not run the models due to insufficient data.

    Model and Data

    Years

    Interest Rate(%)

    Agricultural Food Prices(Rs./40kg)

    Exchange Rate(Rs./US$)

    2000-01

    13.97

    300

    58.43

    2001-02

    12.12

    300

    67.42

    2002-03

    7.58

    300

    58.49

    2003-04

    5.05

    350

    57.56

    2004-05

    8.21

    400

    54.49

    2005-06

    9.93

    415

    59.85

    2006-07

    10.32

    425

    60.62

    2007-08

    12.75

    625

    62.54

    2008-09

    14.32

    950

    78.49

    2009-10

    13.22

    950

    83.79

    2010-11

    14.25

    950

    85.49

    2011-12

    13.13

    1050

    89.23

     

    All the data have been taken from economic survey of Pakistan and State Bank of Pakistan and economic survey’s of Pakistan.

    AFP=f (IR, EX)

    Where,

    AFP= Agricultural Food Prices,

    IR= Interest Rate,

    EX= Exchange Rate

    A= IR+EX

    We performed co integration tests with the Johansen method, using EViews 6, which is designed to test the restrictions imposed by co integration on the unrestricted vector auto regression (VAR) model. The VAR model is estimated with the method of full information maximum likelihood, and the procedure has the advantage of permitting the joint determination of variables in the system, it takes into account the short-run dynamics of the variables, whilst permitting the system of variables to return to long-run equilibrium.

    Johansen’s Co integration Test results

     

    Included observations: 10 after adjustments

    Trend assumption: Linear deterministic trend

    Series: AFP EX IR 

     

    Lags interval (in first differences): 1 to 1

     

    Unrestricted Cointegration Rank Test (Trace)

     

     

     

     

     

     

     

     

     

     

     

    Hypothesized

     

    Trace

    0.05

     

    No. of CE(s)

    Eigenvalue

    Statistic

    Critical Value

    Prob.**

     

     

     

     

     

     

     

     

     

     

    None *

     0.970763

     57.66324

     29.79707

     0.0000

    At most 1 *

     0.876963

     22.34002

     15.49471

     0.0040

    At most 2

     0.129539

     1.387319

     3.841466

     0.2389

     

     

     

     

     

     

     

     

     

     

     Trace test indicates 2 cointegrating eqn(s) at the 0.05 level

     * denotes rejection of the hypothesis at the 0.05 level

     **MacKinnon-Haug-Michelis (1999) p-values

     

     

     

     

     

     

    Unrestricted Cointegration Rank Test (Maximum Eigenvalue)

     

     

     

     

     

     

     

     

     

     

    Hypothesized

     

    Max-Eigen

    0.05

     

    No. of CE(s)

    Eigenvalue

    Statistic

    Critical Value

    Prob.**

     

     

     

     

     

     

     

     

     

     

    None *

     0.970763

     35.32322

     21.13162

     0.0003

    At most 1 *

     0.876963

     20.95270

     14.26460

     0.0038

    At most 2

     0.129539

     1.387319

     3.841466

     0.2389

     

     

     

     

     

     

     

     

     

     

     Max-eigenvalue test indicates 2 cointegrating eqn(s) at the 0.05 level

     * denotes rejection of the hypothesis at the 0.05 level

     **MacKinnon-Haug-Michelis (1999) p-values

     

     

     

     

     

     

     Unrestricted Cointegrating Coefficients (normalized by b’*S11*b=I): 

     

     

     

     

     

     

     

     

     

     

    AFP

    EX

    IR

     

     

    -0.013401

     0.259277

     0.339106

     

     

    -0.012341

     0.326049

    -0.590707

     

     

    -0.014413

     0.546668

    -0.650430

     

     

     

     

     

     

     

     

     

     

     

     

     

     

     

     

     

     Unrestricted Adjustment Coefficients (alpha): 

     

     

     

     

     

     

     

     

     

     

     

    D(AFP)

     31.01838

    -32.70367

    -26.03205

     

    D(EX)

    -0.003105

    -2.648499

    -0.260678

     

    D(IR)

    -1.583446

     0.027244

    -0.379758

     

     

     

     

     

     

     

     

     

     

     

     

     

     

     

     

    1 Cointegrating Equation(s): 

    Log likelihood

    -84.38250

     

     

     

     

     

     

     

     

     

     

     

    Normalized cointegrating coefficients (standard error in parentheses)

    AFP

    EX

    IR

     

     

     1.000000

    -19.34721

    -25.30405

     

     

     

     (1.07052)

     (4.54079)

     

     

     

     

     

     

     

    Adjustment coefficients (standard error in parentheses)

     

    D(AFP)

    -0.415685

     

     

     

     

     (0.48244)

     

     

     

    D(EX)

     4.16E-05

     

     

     

     

     (0.01750)

     

     

     

    D(IR)

     0.021220

     

     

     

     

     (0.00654)

     

     

     

     

     

     

     

     

     

     

     

     

     

     

     

     

     

     

    2 Cointegrating Equation(s): 

    Log likelihood

    -73.90615

     

     

     

     

     

     

     

     

     

     

     

    Normalized cointegrating coefficients (standard error in parentheses)

    AFP

    EX

    IR

     

     

     1.000000

     0.000000

    -225.4642

     

     

     

     

     (20.5497)

     

     

     0.000000

     1.000000

    -10.34568

     

     

     

     

     (0.99779)

     

     

     

     

     

     

     

    Adjustment coefficients (standard error in parentheses)

     

    D(AFP)

    -0.012083

    -2.620661

     

     

     

     (0.59928)

     (13.7032)

     

     

    D(EX)

     0.032727

    -0.864346

     

     

     

     (0.01001)

     (0.22883)

     

     

    D(IR)

     0.020884

    -0.401668

     

     

     

     (0.00888)

     (0.20313)

     

     

     

     

     

     

     

     

     

     

     

     


    Conclusions

    Pakistan has been facing a significant increase in food prices for the past decade. Food price volatility increases the uncertainty faced by farmers and affect their investment decisions. This has important implications for the farm debt, farm incomes and agricultural productivity. Thus, the stabilization of macro prices is fundamental to the long-term restructuring. In this paper shocks to Exchange rate, interest rate were tested and the impact of these shocks on agricultural food prices was tested using VECM. Kargbo(2005) argues that declining food production, high food prices and foreign exchange constraints lower food consumption at the household level. If the prices are not controlled then Pakistan may face these challenges.

    About Authors:

    1) Muhammad Rizwan Altaf is student of B.Sc(Hons), Department of Entomology,University of Agriculture,Faisalabad. He is also affiliated with Agrihunt as an Author. 

    rizwanaltaf75@yahoo.com

    +92 3002122073

     

    2- Muhammad Najaf Ali Maswan is student of  BSc (hons) Economics in F.C College University,Lahore:


    Contact no:0308-7410741
    email: najafmaswan@gmail.com

     

    NOTE:

    If you wanna to publish yours’ articles than plz do contact:  

    uafinformation@yahoo.com 0303-4309053

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