Empirical Analysis of Effects of Expected Inflation on Stock Returns

We adopted asymmetric test specification model to investigate implications of expected inflation on stock returns. While to calculate expected inflation, two methods, Fama money demand model (1981) and ARMA model were employed. Monthly data is obtained covering data span of August 1998 to June 2018 from concerned sources. The results show a strong relationship between real stock returns (adjusted from inflation) and expected inflation while utmost an insignificant relationship between nominal stock returns and predicted inflation. An inverse relationship amidst stock returns and inflation is observed during only low inflation time period in contrast to high inflation time period (positive relationship). The impact of expected inflation on stock returns by dividing the sample period into sub periods provides insignificant relationship between stock returns and expected inflation which is obvious as stock returns behaves noisy in short time period

Inflation Forecasting under Different Macroeconomic Conditions: A Case Study of Pakistan

Inflation forecasting is of primary importance not only for the conduct of monetary policy, but also for individuals to make choices. Forecasting inflation provides the precise image of how the economy is expected to accomplish in the future. For forecasting inflation, personal consumption expenditure is used to measure inflation because of its superiority of less sensitivity of price shock and its revision in subsequent years. For inflation forecasting, naive model, ARIMA model, Philips curve model, and Philips curve threshold autoregressive model are applied under different macroeconomic conditions with real-time, revised and final data from 1974 to 2016. The result shows that the naive model is superior to other models because RMSE and MAE of naive model are smaller than other models by using real-time, revised and final data for one year-ahead out-of-sample inflation forecasting. However, for two years ahead out of the sample inflation forecast, the real-time data RMSE shows that the naive model outperforms the other models, whereas the MAE shows that Philips curve threshold autoregressive model is superior than other models. For revised and final data for two years ahead out-of-sample inflation forecasting both forecasting accuracy measures show the naive model performance is the best. JEL Classification Codes: C5

Price Setting Behaviour of Pakistani Firms: Evidence from Four Industrial Cities of Punjab

Since the introduction of rational expectations in the literature, most of the research focus in the area of macroeconomics has been investigating micro foundations of macroeconomic theory and transmission channels of policy. In 1990s, macroeconomists started working on macro models incorporating the assumption of nominal rigidity with explicit modeling of optimal behaviour of individuals and firms. More recently, these models gained empirical support by looking at both aggregate as well as at firm-level data. In this regard, limited studies are available that focus on developing countries. For Pakistan, there has been little focus on micro level studies in the field of macro or monetary economics, so our study attempts to fill this gap. Besides capturing price setting behaviour, the potential effects of changes in financial cost on the overall pricing and production decisions have also been investigated. It is important to note that this study is different from others throughout carried in different countries in the sense that instead of sending questionnaires by mail, data are collected by enumerators and field supervisors. It was found that Pakistani firms perceive to be in competitive environment they operate in. Most of the clients of the firms are regular and firms’ relationship with the customers is long-term. The large majority of firms use current information when reviewing prices. Around 70 percent of firms use either a state-dependent pricing rule or combination of both time-dependent and state-dependent rules. Pakistani firms revise and change their prices usually in the months of June and July. Moreover, costs of raw materials, cost of energy and inflation are the main determinants of price increase while the competitors’ price, raw materials costs and demand changes are responsible for price decrease. When it comes to the main causes of price stickiness, implicit contract with the customers is at the top, while explicit fixed term contract of prices on the second. Further it was observed that most of the firms change their wages once in a year. About half of the firms index their workers’ wages with inflation and past inflation rate is usually used for the purpose. Labour productivity and changes in inflation rate are found to be the main causes of wage change.Price Setting Behaviour, Effectiveness of Monetary Policy, Wage and Price Contracts

Government Debt and Corporate Leverage: Sectoral Analysis of Pakistan

This study examined the effect of government debt on corporate leverage and analyzed the impact of government debt on all firms at sectoral level enlisted in Pakistan Stock Exchange (KSE-100). For this purpose, it analyzed the panel data of the selected firms from 2006 to 2018. The study utilized the fixed effect linear regression model as determined by the Hausman test. Two variables (book leverage and market leverage) were used to measure corporate leverage. One variable (debt-to-capital ratio) was used to measure debt ratio, while six control variables (market-to-book ratio, GDP per capita, inflation, unemployment rate, tangibility, and return on assets) were used to identify the impact of government debt on corporate leverage and corporate debt. The results of this study revealed that government debt is negatively associated with corporate leverage and has a significant association with the debt ratio of firms. It was also noted that the control variables significantly affect the corporate leverage and debt ratio of firms. These findings have significant implications for the financing decisions of firms

The Unreliability of Output-Gap Estimates in Real Time

Most research on monetary policy assumes availability of information regarding the current state of economy, at the time of the policy decision. A key challenge for policy-makers is to find indicators that give a clear and precise signal of the state of the economy in real time—that is, when policy decisions are actually taken. One of the indicators used to asses the economic condition is the output gap; and the estimates of output gap from real time data misrepresents the true state of economy. So the policy decisions taken on the basis of real time noisy data are proved wrong when true data become available. Within this context we find evidence of wrong estimates of output gap in real time data. This is done by comparing estimates of output gap based on real time data with that in the revised data. The quasi real time data are also constructed such that the difference between estimates of output gap from real time data and that from quasi real time data reflects data revision and the difference between estimates of output gap from final data and that from quasi real time data portray other revisions including end sample bias. Moreover, output gap is estimated with the help of five methods namely the linear trend method, quadratic trend method, Hordrick-Prescott (HP) filter, production function method, and structural vector autoregressive method. Results indicate that the estimates of output gap in real time data are different from what have been found in final data but other revisions, compared to data revisions, are found more significant. Moreover, the output gap measured using all the methods, except the linear trend method, appropriately portray the state of economy in the historical context. It is also found that recessions can be better predicted by real time data instead of revised data, and final data show more intensity of recession compared with what has been shown in real time data. JEL Classification: E320 Keywords: Data Uncertainty, Measurement Uncertainty, Output Gap, Business Cycle, Economic Activit

New Keynesian Phillips Curve for Pakistan

Recently macroeconomists have moved to a new neo-classical synthesis by integrating Keynesian features like imperfect competition and nominal rigidities with dynamic stochastic general equilibrium model of the Real Business Cycle Theory with micro foundations and rational expectations, [see, for instance, McCallum and Nelson (1999)]. The standard model comprises of a trinity; consumption and inflation adjustment equations with a monetary authority’s reaction function. One of the pillar of the modelinflation adjustment equation, also known as New Keynesian Phillips Curve (NKPC) in the literature, has at least two important features; unlike the traditional Phillips curve the NKPC is forward-looking; and it has been derived from the profit maximising behaviour of the firms in a monopolistically competitive market structure

Revisiting the macroeconomic variables and economic growth nexus: A Markov regime-switching approach

Purpose ―Current paper assesses the impact of macroeconomic variables on Pakistan's economic growth. Method ― This study analyzed the data using the Markov Regime switching (MS) model using monthly data for 1981-2020. Firstly, BDS and CUSUM square tests were applied to detect the non-linearity of the model. Results ―The model is non-linear, so the Markov regime-switching model is used for analysis. Each regime's mean and variance are highly significant and show a high growth regime with high volatility and a low growth regime with low volatility. Furthermore, the results show that inflation, interest rate, and trade openness negatively impact while real effective exchange rates positively affect development in both regimes. The negative effect of interest rate, exchange rate, inflation, and trade openness become more pronounced in low growth regimes. Implication ― This study suggests that policymakers should consider the non-linear behaviour of macroeconomics. This will help to formulate better policies for the economy's economic growth. Originality ―The current research adds to the existing literature by identifying the non-linear effect of growth indicators on economic growth, which was previously neglected in the case of Pakistan

Price Setting Behaviour of Pakistani Firms: Evidence from Four Industrial Cities of Punjab

PAKISTAN INSTITUTE OF DEVELOPMENT ECONOMIC