Analysis of Migration of Advertisement Business from Print Media to Electronic Media of Pakistan: A Time Series A.R.I.M.A Model Application for Forecasting Overall Print Industry’s Advertisement Business Curtailment

Ovais Abdur Rehman; Asif Naji

摘要

Couple of decades back, it was generally acceptable that print media has secured future, newspapers and magazines have a good market and good readership in Pakistan. But by the end of 90’s, when electronic media introduced and welcomed by peoples, print industry of Pakistan tends to decline and players of the industry was in shocked and started to take steps to survive in the market. Advertisers are curtailing their advertisement business from print media and allocating more budgets to advertiser in electronic media. Purpose The purpose of the study is to highlight the future trend and to forecast the future share of publishers in market’s total advertisement business by using autoregressive integrated moving average (ARIMA) models. Design/Methodology/Approach This research is divided into two parts; in part one, data about the print media share in total advertisement business is collected from the head office of APNS. In part two is Box-Jenkins approach of ARIMA modeling was applied on the time series data to forecast. In this study, framework of ARIMA includes the following steps: Data collection, identification of model and order, making data stationary, estimation of different orders of ARIMA models to find the best appropriate model by comparing their AIC and SIC values, diagnostic test of residuals for white noise and forecasting of in-sample and out sample data. Findings The traditional Box-Jenkins methodology was used to forecast the time series named ARIMA modeling. Initially the model which was identified was AR(1), by the spikes of the correlogram and used to build up the model. Correlogram of basic data series showed the existence of unit root in the series but on 1st level of difference, the data series became stationary. Augmented Dickey Fuller Unit Root test was applied to accept or reject the hypothesis of unit root, and on first differentiation the value of t was -4.83 which is significant and the null hypothesis of unit root existence was rejected and series considered as stationary. ARIMA (2,1,3) was identified as the best appropriate model with lowest AIC and SIC value among 15 combinations of AR and MA which were estimated in this study. Yt = α + Φ1Yt- 1 + Φ2Yt- 2 + θ1et-1 + θ2et-2 + θ3et-3 Yt = -0.0798 - 0.1184Yt- 1 + 0.1012Yt- 2 - 1.5085et-1 - 26.14et-2 - 13.46et-3 Equation of ARIMA (2,1,3) shows that the today print media’s advertisement revenue share is dependent on the two leg value of past year’s share value and on the three leg values of past years error which is moving average. The value of R2 is 0.9988 which shows that the model is fit and the weight of auto regressive and moving average legs in total sum of square is around 99%. Correlogram Q Statistics of residuals, shows that the residuals are white noise and model is pass the suggested diagnostic test. The forecasting of 2013, which is in sample data shows the same result as per actual data so the prediction power of model is considered as reliable and appropriate. The future prediction which is out of sample prediction shows the 6 percent decline in the share of print media in advertisement revenue over the period of four years which is an alarming situation for the publishers. Readers are switching from printed stuff to online stuff and in Pakistan; people are more likely to watch television therefore advertisers of Pakistan are more interested to advertise in electronic media and they are curtailing their advertisement expense from print media and allocating more budget to electronic media. Practical Implications This study will help new comers in this industry of publishing in Pakistan to understand the advertisement revenue trend and also to understand the ARIMA model application. It also helps the existing publishers to make vital decision regarding the revenue mix and to take any grand decision like diversification or merger etc. Originality/Value This study is unique; it is quantitative in nature. All the data in this paper is original and secondary data was collected from the head office of All Pakistan Newspaper Society which is the main governing body of print media in Pakistan. This study predicts about the future of the industry because the main factor of profitability of print media which is advertisement income is predicted.

机译：几十年前，人们普遍接受印刷媒体确保未来的发展，报纸和杂志在巴基斯坦拥有良好的市场和良好的读者群。但是到了90年代末，当电子媒体受到人们的欢迎和欢迎时，巴基斯坦的印刷业趋于衰落，该行业的参与者感到震惊，并开始采取措施在市场上生存。广告商正在缩减其从印刷媒体中获得的广告业务，并向电子媒体中的广告商分配更多预算。目的研究的目的是通过使用自回归综合移动平均（ARIMA）模型来突出未来趋势，并预测发布商在市场总广告业务中的未来份额。设计/方法论/方法这项研究分为两个部分;第二部分是设计。在第一部分中，从APNS总部收集有关印刷媒体在全部广告业务中所占份额的数据。第二部分是将ARIMA建模的Box-Jenkins方法应用于时间序列数据进行预测。在这项研究中，ARIMA的框架包括以下步骤：数据收集，模型和顺序的标识，使数据稳定，估算ARIMA模型的不同顺序，以通过比较AIC和SIC值找到最佳的合适模型，残差的诊断测试用于白噪声和样本内和样本外数据的预测。发现传统的Box-Jenkins方法用于预测称为ARIMA建模的时间序列。最初，通过相关图的峰值识别出的模型为AR（1），并用于构建模型。基本数据序列的相关图显示该序列中存在单位根，但在第一级差异上，数据序列变得平稳。应用增强的Dickey Fuller单位根检验接受或拒绝单位根的假设，并且在初次微分时，t的值为-4.83，这是显着的，单位根存在的零假设被拒绝，并且系列被认为是平稳的。在本研究中估计的15种AR和MA组合中，ARIMA（2,1,3）被确定为AIC和SIC值最低的最佳模型。 Yt =α+Φ1Yt-1+Φ2Yt-2+θ1et-1+θ2et-2+θ3et-3Yt = -0.0798-0.1184Yt-1 + 0.1012Yt-2-1.5085et-1-26.14et-2-13.46et -3 ARIMA（2,1,3）的等式表明，当今印刷媒体的广告收入份额取决于去年份额的两个支腿价值和过去几年的误差的三个支腿价值，即移动平均数。 R2的值为0.9988，表明该模型是合适的，并且自回归和移动平均边的权重在总平方和中的权重约为99％。相关图Q残差的统计量，表明残差是白噪声，并且模型通过了建议的诊断测试。样本数据中的2013年预测显示与实际数据相同的结果，因此该模型的预测能力被认为是可靠且适当的。超出样本预测的未来预测表明，在四年内，印刷媒体在广告收入中所占的份额下降了6％，这对于发布者来说是一个令人震惊的情况。在巴基斯坦，读者正在从印刷品转向在线品。人们更喜欢看电视，因此巴基斯坦的广告客户对在电子媒体上投放广告更加感兴趣，他们正在削减印刷媒体的广告费用，并向电子媒体分配更多预算。实际意义该研究将帮助巴基斯坦出版业的新手了解广告收入趋势，并了解ARIMA模型的应用。它还可以帮助现有的发布者做出有关收入组合的重要决策，并做出诸如多元化或合并等任何重大决策。它本质上是定量的。本文中的所有数据均为原始数据，次要数据是从全巴基斯坦报纸协会的总部收集的，该协会是巴基斯坦印刷媒体的主要管理机构。这项研究预测了该行业的未来，因为预测了印刷媒体盈利能力的主要因素，即广告收入。

Analysis of Migration of Advertisement Business from Print Media to Electronic Media of Pakistan: A Time Series A.R.I.M.A Model Application for Forecasting Overall Print Industry’s Advertisement Business Curtailment

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