Shodhyantri Engineering Services
Research · Analysis · Editing · Publication Support
Stationarity tests, ARDL, VAR, VECM and volatility models run in EViews, with diagnostics and interpretation you can explain to your examiner.
Tell us about your eviews econometrics need. We reply within one working day.
EViews econometric analysis is a common choice for economics, finance and commerce theses built on time series or panel data. Shodhyantri supports scholars in choosing the right model sequence, running it correctly in EViews, and reading the output with care. We work on macroeconomic series, stock returns, commodity prices, trade data and state-level panels drawn from sources such as RBI, MOSPI, World Bank and NSE.
Most errors in time series theses come from skipping steps: no stationarity test, wrong lag length, or a cointegration test applied to series of the wrong order. We follow a documented sequence, record every test and explain what each result means for your hypotheses. Your economic reasoning and the writing stay yours. We make sure the econometrics underneath is sound and defensible.
EViews is commercial econometrics software from S&P Global, widely taught in Indian economics and finance departments. It handles dated workfiles, frequency conversion, lag operators and a large set of estimators through menus and a command language, which makes time series work faster than in general statistics packages.
A typical thesis workflow runs from data preparation and descriptive statistics to unit root tests, model selection, estimation, diagnostic checks, stability tests and forecasting or impulse response analysis. The model chosen depends on the integration order of your variables and your research questions.
We decide between OLS, ARDL, VAR or VECM after unit root testing, so the model fits the integration order of your data.
Lag length is chosen with AIC, SIC or HQ criteria and reported, so examiners can see the choice was not arbitrary.
Serial correlation, heteroscedasticity, normality and CUSUM stability tests are run and reported with each final model.
Policy changes such as demonetisation or GST can break series. We test for breaks where your period suggests one.
We explain coefficients, error correction terms and impulse responses in plain terms so you can link them to theory.
EViews output is converted into concise tables with standard errors, significance markers and test statistics for your chapter.
Ten stages, each with a clear output. Nothing moves to the next stage until you have reviewed the last one.
— You review every stage first, then decide —
Each variable is checked against its source for units, base year changes and gaps.
No series is I(2) where ARDL is used, and all are I(1) for Johansen tests.
Serial correlation LM, Breusch-Pagan and Jarque-Bera tests are reviewed before results are accepted.
CUSUM and CUSUM of squares plots confirm parameters are stable across the sample period.
Coefficient signs are compared with economic theory and unexpected signs are flagged for discussion.
The EViews program reproduces every result from the raw workfile without manual steps.
Every stage is shared with notes explaining what was changed and why. You and your supervisor check it, and the next stage starts only after your go-ahead.
| Common problem | How Shodhyantri helps |
|---|---|
| Running OLS on non-stationary series and reporting a high R-squared as strong evidence. | We test stationarity first and use ARDL, VECM or differenced models so spurious regression is avoided. |
| Applying the ARDL bounds test when one variable is integrated of order two. | We confirm no series is I(2) before ARDL, and choose another approach or transformation if one is. |
| Choosing lag length by habit, such as always using two lags. | Lags are selected by AIC, SIC or HQ and then confirmed with residual serial correlation tests. |
| Reading Granger causality as proof of economic cause and effect. | We explain it as predictive precedence and help you word conclusions carefully in your discussion chapter. |
| Mixing data series with different base years without rebasing them. | Series such as GDP or price indices are spliced or rebased consistently before any estimation begins. |
| Skipping diagnostic tests and stability checks after estimating the final model. | Every final model is reported with serial correlation, heteroscedasticity, normality and CUSUM results. |
A simple line graph shows trends, breaks and outliers that tell you which unit root test specification to use.
Log-transformed variables let you read long-run coefficients as elasticities, which is easier to explain in a viva.
EViews command programs record every step. They make revisions quick when your supervisor asks for a new period.
Using two unit root tests with different assumptions strengthens your conclusion about integration order.
In ARDL-ECM and VECM the error correction term should be negative and significant for adjustment to equilibrium.
Annual data over twenty years gives few degrees of freedom. Keep lags and variables modest in short samples.
Name the database, table and access date for every series. It helps examiners verify and other researchers replicate.
If your period spans a major policy change, test for structural breaks before trusting a single long-run estimate.
Your work is handled by people who read your field's literature, not by a single generalist.
A PhD-qualified specialist from your field who checks the research logic, gap and contribution.
Handles statistics, models and qualitative coding, and documents every analytical decision.
Improves structure, flow, clarity and academic tone without changing your meaning.
Builds and validates MATLAB, Python, ANSYS or COMSOL work where your study needs it.
Checks grammar, consistency, numbering, citations and the small errors examiners notice.
Applies your university or journal template, reference style and front matter exactly.
ARDL works when variables are a mix of I(0) and I(1), and suits smaller samples. Johansen requires all variables to be I(1) and handles multiple cointegrating relationships. Unit root results decide which applies, and we explain the choice in your methodology.
We guide you to suitable sources such as RBI's Database on Indian Economy, MOSPI, World Bank WDI and IMF data, and help you set definitions and periods. Downloading and verifying the data is usually best done by you, so you can cite it confidently.
Not for the analysis itself. However, to open the workfile and rerun results yourself, you will need access to EViews, often available in university labs. We can also provide outputs in Excel and Word so you can work without it.
No. Results come from your data, and we report them honestly. If a relationship is not significant, that is a finding. We help you interpret and present such results properly, which examiners and reviewers respect more than forced outcomes.
Yes. We run pooled, fixed effects and random effects models, apply the Hausman test, and can perform panel unit root and panel cointegration tests where your panel has enough time periods. We also test for cross-sectional dependence where the panel structure suggests it, and explain each result.
No. We provide tables, graphs and interpretation notes, and explain results on a call. You write the chapter in your own words. We can then review your draft for correct reporting and econometric accuracy. This keeps authorship clearly with you.
Yes. We also work in Stata and R. If your supervisor prefers a different package, we run the same models there, or reproduce EViews results so both match and the methodology section names the software actually used.
We provide research guidance, statistical analysis, editing, formatting and training support. All research content remains the scholar's own work, in line with UGC and university academic integrity norms. We do not guarantee publication, acceptance, indexing or academic outcomes: journals decide through peer review and universities award degrees.
Share your topic, draft or data. We will tell you honestly what it needs, and what it does not, before you pay anything.