big data application to predict macroeconomic indicators - statswork

Research paper

BIG DATA APPLICATIONTO PREDICTMACROECONOMICINDICATORS

Research Planning | Data Collection | Semantic Annotation | BusinessAnalytics | Bio Statistics | Econometrics

Data collection, macroeconomic conditions, Big Data, Traditional BusinessSystems, The Internet of Things, Bayesian vector autoregression, VARmodel in economics

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INTRODUCTION

Private agencies and governmentinstitutions are collecting and

unifying information on several aspects of the economy, and over

the period the opportunity of datacollection has sufficiently grown,

and therefore the quality ofdata has been enhanced.

Monitoring ofmacroeconomic conditions has

become the regular job of devotedeconomists at private institutions,

banks, and governmentagencies, who scrutinize

through big and complex data torefine all vital information.

Research Planning | Data Collection | Semantic Annotation | Business Analytics | Bio Statistics | Econometrics Copyright © 2019 Statswrok. All rights reserved

http://www.statswork.com/services/data-collection-coding-management/

http://www.statswork.com/services/data-collection-coding-management/

http://statswork.com/blog/how-data-from-online-reviews-and-macroeconomic-indicators-can-be-used-to-predict-product-sales-forecast/

Social NetworksTraditional Business SystemsThe Internet of Things

An apt place for a calculation of the prospective welfares and expenses of the Big Data use formacroeconomic prediction is the identification of the source. Key source for big data are:1.2.3.


Identification of Sources for Big Data


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A foremost source is signified not only by human-sourced informationotherwise known as Social Networks, which mainly explain to includesocial networking, but also e-mails, internet searches, comments, blogs,videos, pictures, etc.

The allied data is roughly organized and frequently ungoverned.


Social Networks


Big Data’s second key source is process mediated data, otherwisecalled as Traditional Business Systems (TBS).

These developments track and observe the interest of businessevents, like accepting an order, record keeping of a customer,manufacturing a product, etc.

TBS data is the massive majority of what IT achieved and handled,in both business intelligence and operational systems.

Generally, designed and deposited in database systems can befurther assembled into data shaped by businesses and publicagencies.


Traditional Business Systems


https://journals.sagepub.com/doi/abs/10.1111/j.1741-6248.2008.00115.x

The third source is the fast-expanding benefactor of Big Data, known as the Internet of Things (IoT).

This data is derivate from machines which are used to track and calculate occasions and progress in themodern era.

The concise way of data generated from the machine is apt for computer processing, but its sizedemands the usage of new statistical methodologies.


Internet of Things


http://statswork.com/blog/model-based-clustering-using-bayesian-approach-for-binary-panel-probit-models/

Looking from the viewpoint of economic prediction, all these abovementioned three types of Big Data are theoretically related.

For instance, selected social networks, IoT, TBS could all give relevantleading indicators for Gross Domestic Product growth of a nation.

So, a vital step for the usage of Big Data for prediction is anarrangement of selected data, along with the features of the targetedvariable.


Interrelation Between theSources of Big Data



Big Data can be implemented and categorized once it is temporally designed and well cleaned.

This can implement several econometric procedures to equalize the target indicator with variables of Big Data.

After the implementation, sample cross-validation of the substitute methodologies can be conducted.

A conjoint method for the ventilated data is to either execute expectations or collect the data on theeconometric models.

Without any doubt, these expectations are not valid, and aggregation of data leads to a loss of data. So, BigData econometrics is mandatory.

Designing Big Data Strategy

Bayesian vector autoregression (BVAR) Vector auto regressions (VARs)

There are two frameworks for monitoring Macroeconomic Indicators using Big Data:


Framework for Monitoring MacroeconomicIndicators Using Big Data


In real-time, for monitoring macroeconomy and prediction with big data, Bayesian vector autoregression(BVAR) deals with a substitute modeling framework.

In BVARs, all the variables are independent when combined with this high level of complexity.

BVARs are also applicable for prediction since they can perform in a space form letting for accessiblytreating data with the help of filtering procedures.

This is a significant way of study since Bayesian inference delivers a coherent model framework that canbe misused to lessen the number and significance of subjective choices like the transformation of data.


Bayesian Vector Autoregression (BVAR)


http://statswork.com/blog/model-based-clustering-using-bayesian-approach-for-binary-panel-probit-models/

Vector auto regressions (VARs) are the most linear framework and are broadly used inmacroeconomics.

In VAR each and every variable hinge on its past and the outline of connection of the forecast faults indifferent variables is left unrestricted.

VAR model in economics has already been backed by the primary exponents of these models.

According to a recent study, it’s resulted that they are firmly allied with factor models and are appropriatefor the scrutiny of big data.


Vector Auto Regressions (VARs)


https://www.sciencedirect.com/science/article/pii/S0165188901000410

CONCLUSIONCopyright © 2019 Statswrok. All rights reserved

Generally, we tend to assure that Big Data is appreciated in an exceeding nowcasting framework, not onlyto cut back the errors but to boost the suitability, occurrence of release and scope of data.

The combination of the architecture in the present organizational systems is a perilous procedure to ensurethe period of forecasts and nowcasts.

The implementation of the frameworks in an apt cloud computing situation so that the operation canbalance easily is also critical.



Strategy to implement the anticipated Big Data architecture topublish and create real-time predictions and forecasts of somemacro-economic models using Internet data.

Future Scope

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Research Planning | Data Collection | Semantic Annotation | Business Analytics | Bio Statistics | Econometrics Copyright © 2019 Statswork. All rights reserved