The BECE 142 Solved Guess Paper is a 16 page PDF built for one job only: getting you through the Applied Econometrics term end paper of the B.A. (Honours) Economics programme without drowning in the four blocks of the IGNOU book. It carries 13 questions with complete written answers, mapped block by block, and every question on the list has been chosen after reading the actual BECE 142 question papers from June 2023 through December 2025.
Five of those 13 answers are printed in full further down this page. Read them, judge the writing for yourself, and if the standard suits you, the remaining eight answers come to you on WhatsApp as a single PDF. Nothing is hidden behind vague claims. What you see in the samples is exactly what the rest of the file looks like.
BECE 142 guess paper at a glance
- Course code and title: BECE 142, Applied Econometrics
- Programme: B.A. (Honours) Economics, BAECH
- Credits: 6 credits
- Questions in the file: 13 questions with full answers
- Sample answers on this page: 5 of 13, printed in full
- Answers delivered after enquiry: Remaining 8 questions
- File length: 16 pages, of which 13 pages are answers
- Blocks and units covered: 4 blocks, 12 units
- Papers analysed: 6 sessions, June 2023 to December 2025
- Topics tracked in the frequency table: 26 recurring topics
- Exam duration and marks: 3 hours, 100 marks
- Target session: December 2026 term end examination
- Medium: English
- Delivery: PDF on WhatsApp 9899436384
Key facts about the BECE 142 Applied Econometrics guess paper and its term end examination.
What you get in the BECE 142 Applied Econometrics guess paper pack
You get one PDF of 16 pages containing 13 exam style questions and 13 pages of written answers, plus an exam pattern sheet, a do not prepare list and a six session frequency table. There is no second file, no login and no course portal to navigate. The document opens on any phone.
The 13 questions are not a random selection. Four of them sit in Section A at 20 marks each, seven sit in Section B at 12 marks each, and two are short note sets worth 6 plus 6 marks. That mirrors the shape of the paper you will actually sit, which means your revision time is distributed the way the marks are distributed rather than spread evenly over topics that carry unequal weight.
Each answer follows the same internal skeleton. A quoted definition from the IGNOU block comes first, because examiners look for the technical vocabulary in the opening lines. Numbered points follow, since consequences, steps, features and conditions are what the Applied Econometrics paper keeps asking for. A short evaluative conclusion closes the answer so the script does not simply stop mid thought.
Students who are collecting material for more than one paper this session usually pick up the wider IGNOU Solved Guess Paper collection at the same time, since the same method has been applied to the other BAECH courses and the format stays identical across codes.
Sample questions and answers from the BECE 142 Solved Guess Paper
Five of the 13 answers are reproduced below word for word, exactly as they appear in the PDF. They cover all three sections of the paper and all three mark weights, so you can judge the 20 mark, 12 mark and 6 mark writing separately before deciding anything.
Inclusion of an irrelevant variable versus omission of a relevant variable
Question: Show why it is better to err by including an irrelevant variable as compared to omitting a relevant variable in a regression model.
Meaning of specification errors
Unknowingly, we commit specification errors like omitting a relevant variable or including an irrelevant variable in the model, due to which the regression estimates could be affected.
Consequences of omitting a relevant variable
If a variable that is truly relevant is dropped from the model, the estimates are seriously distorted in the following ways:
- The omitted variable produces an omitted variable bias, so the OLS coefficients become biased; the direction of bias depends on how the omitted variable correlates with the dependent and the included variables.
- The estimates are also inconsistent, since even in large samples they remain biased.
- If the included and omitted variables are unrelated in the sample, the slope is unbiased and consistent, but the intercept stays biased unless the omitted variable's mean is zero.
- The error variance is estimated wrongly, so the variance of the slope coefficient is overestimated.
- As a result, the confidence interval and the hypothesis testing results become unreliable.
Consequences of including an irrelevant variable
Over specifying a model by adding an unnecessary variable does not damage its basic properties:
- The OLS estimators remain unbiased and consistent even after the irrelevant variable is included.
- The confidence interval and the hypothesis testing procedure remain valid.
- The estimator of the error variance is unbiased and correctly estimated.
- The only negative consequence is a loss of efficiency, as the variance of the slope coefficient becomes larger, depending on how close the correlation between the regressors is to +1 or minus 1.
Why inclusion is the lesser error
Omitting a relevant variable makes the estimates biased, inconsistent and inefficient, invalidating the usual t and F testing procedures. Including an irrelevant variable keeps the estimators unbiased and consistent and the tests valid, sacrificing only efficiency. Hence it is the lesser of the two errors, though it costs both efficiency and degrees of freedom; the best practice is to include only theoretically justified variables.
Conclusion: Omission damages bias, consistency and validity together, whereas inclusion harms only efficiency. Therefore it is safer to err by including an irrelevant variable than by omitting a relevant one.
Effect of lags on market equilibrium
Question: Discuss the effect of lags on market equilibrium with suitable examples.
Meaning of lags
Lags are nothing but time related delays between cause and effect. There is always some time lag between a cause and its effect. Because production and adjustment take time, the effect of a change in the market is perceived only after a delay, which makes the study of lags central to economics.
The cobweb model of market equilibrium
Consider a single good whose supply and demand for period t are:
- Supply depends on the previous period's price, St = α1 + β1Pt−1, since producers decide output on the basis of last period's price.
- Demand depends on the current price, Dt = α2 + β2Pt, where the supply slope β1 is greater than zero and the demand slope β2 is less than zero.
- Price is set each period to clear the market, but since supply adjusts only after a lag, the equilibrium is reached gradually rather than instantly.
Because the slopes carry opposite signs, the path traced by observed price and quantity resembles a cobweb, and hence the model of market instability is called the cobweb model.
How the lag drives equilibrium behaviour
- Setting demand equal to supply gives a first order non homogeneous difference equation whose solution has a particular integral, the inter temporal equilibrium price, and a complementary function.
- The equilibrium price is positive and invariant over time; it is the price at which demand equals supply across periods.
- The actual price in each period is the equilibrium price plus a term involving the ratio (β1/β2) raised to the power of time, which determines whether the price converges to, oscillates around, or diverges from equilibrium.
Illustrations of the lag effect
The relative income hypothesis shows present consumption depending on past consumption; the accelerator theory links investment to past changes in consumption; and energy or durable goods demand depends on accumulated past stocks and incomes.
Conclusion: Because supply reacts to past prices while demand reacts to current prices, lags force the market to adjust gradually. The cobweb model shows that depending on the relative slopes, lagged adjustment can make price converge to, oscillate about, or move away from equilibrium.
Ramsey's RESET test
Question: Describe Ramsey's test (RESET) for identification of omitted variables and incorrect functional form.
Meaning of the RESET test
A formal approach was developed to detect the presence of specification errors; the test is called RESET, the regression specification error test.
Steps in the test
- From the incorrectly estimated linear model, first obtain the estimated or fitted values of the dependent variable.
- Re estimate the model after including the higher powers of these fitted values, that is the squared and cubed terms, as extra regressors.
- Treat the original model as the restricted model and the augmented model as the unrestricted model, and note the R squared of each.
- Set the null hypothesis that the restricted model is correctly specified, that is, the coefficients of the added powers are zero.
- Compute the F statistic from the two R squared values with m and (n minus k) degrees of freedom, where m is the number of restrictions, n the observations and k the parameters.
- If the computed F is statistically significant, reject the null and conclude that the model is misspecified.
The intuition is that if adding powers of the predicted variable raises the explanatory power, this is evidence of specification error.
Limitations
- The test does not suggest any alternative specification.
- It gives no guide on the power of the variable to be included in the unrestricted model.
Conclusion: RESET detects omitted variables and incorrect functional form by checking whether powers of the fitted values add explanatory power. A significant F rejects correct specification, though the test neither names the fault nor the corrective power needed.
One way ANOVA in R
Question: Illustrate the procedure for obtaining the results of one way ANOVA in R.
Meaning of one way ANOVA
We can use the one way ANOVA procedure to test the hypothesis that the means of two or more groups are not statistically different. Using data on examination test scores, the test scores are taken as the dependent variable and the type of examination administered, of which there are three types, as the independent variable. The objective is to find whether the scores vary due to the examination type.
Procedure in R
- Enter the test scores for each examination type using the combine function, for example
type1.scores <- c(...), and similarly for type2 and type3. - Combine all the scores into a single vector named Score using
c(type1.scores, type2.scores, type3.scores). - Create a grouping factor Type with the
rep()command, repeating the labels type1, type2 and type3 for the length of each group. - Form a data frame combining Type and Score using
data.frame(Type, Score). - Run the analysis with the command
result <- aov(Score ~ Type, data = data), which produces the ANOVA output table.
Interpreting the output
The output reports the degrees of freedom, sum of squares, mean square, F value and the p value. In the illustration the F statistic is 13.01 with a p value of 0.0001, which is less than 0.05. Hence the null hypothesis of no difference in test scores is rejected, and we conclude that the examination type does make a significant difference to the students' scores.
Conclusion: One way ANOVA in R is run with the aov() command on a data frame of the response and the grouping factor. A p value below 0.05 leads to rejecting the equal means hypothesis, confirming the group factor matters.
Short notes on AIC and pooled cross section data
Question: Write short notes on: (a) Akaike Information Criterion (AIC); (b) pooled cross section data.
(a) Akaike Information Criterion
The Akaike information criterion is an estimator of the relative quality of each model, that is, relative to others.
- In the AIC criterion a penalty is imposed for each additional variable included in the regression model.
- Most software reports the log transformed AIC, in which 2k/n acts as the penalty factor, where k is the number of parameters and n the number of observations.
- AIC imposes a stronger penalty than the adjusted R squared for adding more variables.
- While choosing among models, the model with the lowest value of AIC is preferred.
- It is useful for in sample as well as out of sample forecasting and for choosing the lag length in autoregressive models.
(b) Pooled cross section data
Pooled cross sectional data are obtained by collecting random samples from a large population independently of each other at different points of time.
- Combining separate cross section samples taken in different years increases the sample size.
- For example, separate household surveys of 1985 and 1990 can be pooled into one larger data set.
- Pooling years before and after a policy change is an effective way of analysing the effect of a new government policy.
- It is analysed much like a standard cross section, except that secular differences across time must be accounted for, often using separate intercepts for each period.
Conclusion: AIC ranks models by relative quality, favouring the lowest value, while pooled cross section data combine independent samples from different years to enlarge samples and study policy effects over time.
That is 5 of 13. The remaining 8 answers cover simultaneous equation bias in the Keynesian model, fixed versus random effects, binary dependent variable models, research design versus research methods, indirect least squares, the identification problem, Hausman's procedure and the Koyck and adaptive expectations short notes.
Ask for the remaining 8 answers on WhatsApp 9899436384BECE 142 Applied Econometrics exam pattern and marks distribution
The BECE 142 term end paper runs for 3 hours and carries 100 marks across three sections, and you attempt only 8 questions out of the 15 printed. That choice ratio is the single reason a focused guess paper works for this course.
| Section | Questions printed | Questions to attempt | Marks each | Section total | Word target per answer |
|---|---|---|---|---|---|
| Section A | 4 | Any 2 | 20 | 40 | About 450 words |
| Section B | 7 | Any 4 | 12 | 48 | About 250 words |
| Section C | 4 short note items | Any 2 | 6 | 12 | About 150 words |
| Total | 15 | 8 | — | 100 | — |
Both the English and Hindi versions of the paper are printed in the same booklet and you may answer in either medium. The guess paper is written in English, and students writing in Hindi generally use it for the structure and the point ordering while phrasing the answer in their own medium.
One habit worth building before the exam: read the wording of the same topic across two or three sessions. Section B questions in particular get re cut rather than repeated, so simultaneous equation bias appears once as an analysis question and once as a define and elucidate question. Working through the IGNOU Previous Year Question Paper archive alongside this guess paper is what turns a memorised answer into a flexible one.
Unit wise index of the BECE 142 Applied Econometrics guess paper
BECE 142 has no practical file, laboratory record or project component, so the index below maps the guess paper to the 12 theory units of the four IGNOU blocks instead. If you have been told to submit a practical file for this course, that instruction belongs to a different BAECH paper, not to Applied Econometrics.
| Block | Unit | Core ideas you must be able to write | Guess paper questions |
|---|---|---|---|
| Block 1 · Empirical Issues in Econometric Research | Unit 1 · Stages in Empirical Research | Steps of empirical research, research methodology, the difference between research design and research methods, review of the classical linear regression model | Q6 |
| Block 1 · Empirical Issues in Econometric Research | Unit 2 · Specification Issues | Omitted variable bias, cost of including an irrelevant regressor, errors of measurement in the regressand and the regressor, the RESET diagnostic | Q1, Q7 |
| Block 1 · Empirical Issues in Econometric Research | Unit 3 · Model Selection | Adjusted R squared, AIC, SIC and Hannan Quinn penalties, choosing lag length, in sample versus out of sample forecasting | Q12 (a) |
| Block 2 · Dynamic and Simultaneous Equation Models | Unit 4 · Autoregressive and Distributed Lag Models | Reasons for lags, the cobweb model and market instability, Koyck geometric transformation, adaptive expectations and partial adjustment | Q2, Q13 |
| Block 2 · Dynamic and Simultaneous Equation Models | Unit 5 · Binary Dependent Variable Models | Linear probability model and its four defects, the odds ratio, the logit transformation, probit and the marginal effect | Q5 |
| Block 2 · Dynamic and Simultaneous Equation Models | Unit 6 · Simultaneous Equation Models I | Endogenous and exogenous variables, structural versus reduced form, simultaneity bias in the Keynesian consumption and income system | Q3 |
| Block 2 · Dynamic and Simultaneous Equation Models | Unit 7 · Simultaneous Equation Models II | Under, exact and over identification, order and rank conditions, indirect least squares, why two stage least squares is needed | Q8, Q9 |
| Block 3 · Panel Data | Unit 8 · Introduction to Panel Data | Pooled cross sections versus true panels, degrees of freedom gains, before and after policy comparisons on the same unit | Q12 (b) |
| Block 3 · Panel Data | Unit 9 · Estimation of Panel Data Models | Fixed effect within estimator, random effect and GLS, time invariant regressors, the Hausman specification test | Q4, Q10 |
| Block 4 · Introduction to Econometric Software Packages | Unit 10 · Introduction to R | Vectors and the combine function, building a data frame, running aov() for one way ANOVA, reading the F and p value output | Q11 |
| Block 4 · Introduction to Econometric Software Packages | Unit 11 · Introduction to EViews | Workfile creation, descriptive statistics, running a regression, obtaining panel data regression output | Backup topic |
| Block 4 · Introduction to Econometric Software Packages | Unit 12 · Introduction to Stata | Basic commands, regression diagnostics, tests of significance and hypothesis testing output | Backup topic |
Notice how uneven the coverage is. Blocks 1 and 2 between them supply seven of the thirteen questions, while Block 4 supplies one high value question that almost nobody prepares because it looks like software work rather than economics. That imbalance is deliberate and it comes straight out of the paper history, not from a guess. If you also want the full block reading order and unit summaries, our BECE 142 Study Material page carries that separately.
Six session frequency analysis behind the BECE 142 important questions
Twenty six topics were tracked across the six BECE 142 papers from June 2023 to December 2025, and only nine of them appeared four times or more. Those nine are the backbone of the guess paper; the rest are ranked as medium or low and treated as backup.
| Topic | J 23 | D 23 | J 24 | D 24 | J 25 | D 25 | Priority |
|---|---|---|---|---|---|---|---|
| Binary dependent variable models and the LPM | Yes | Yes | Yes | Yes | Yes | Yes | High |
| Research design versus research methods | Yes | Yes | Yes | Yes | Yes | Yes | High |
| Panel data, fixed effect and random effect models | Yes | Yes | No | Yes | Yes | Yes | High |
| One way ANOVA and diagnostics in R | Yes | Yes | No | Yes | Yes | Yes | High |
| Omission of a relevant or inclusion of an irrelevant variable | No | Yes | Yes | Yes | Yes | No | High |
| Effect of lags on market equilibrium and the cobweb model | Yes | Yes | No | Yes | Yes | No | High |
| Indirect least squares method of estimation | Yes | Yes | Yes | No | Yes | No | High |
| Ramsey's RESET test | Yes | No | Yes | No | Yes | No | High |
| Logit model and its parameters | No | Yes | No | Yes | No | Yes | High |
| Simultaneous equation bias in the Keynesian model | No | Yes | No | Yes | Yes | No | High |
| Significance and factors behind lags | Yes | Yes | Yes | No | No | No | Medium |
| Koyck's approach and transformation | No | No | No | Yes | Yes | Yes | Medium |
| Adaptive expectations, partial adjustment and Nerlove | No | No | No | No | Yes | Yes | Medium |
| Probit model and the marginal effect | No | No | Yes | No | Yes | No | Medium |
| Identification problem, under, over and exact | Yes | No | Yes | No | No | Yes | Medium |
| Hausman's model selection procedure | No | Yes | Yes | No | No | Yes | Medium |
| Pooled cross section data | No | Yes | Yes | Yes | No | No | Medium |
| Model selection criteria, AIC, SIC and adjusted R squared | No | No | Yes | Yes | No | Yes | Medium |
| Quantitative versus qualitative research | No | Yes | No | No | Yes | No | Medium |
| Errors of measurement | Yes | No | No | No | No | Yes | Medium |
| EViews basic functions | Yes | No | Yes | No | No | No | Medium |
| Stata hypothesis and diagnostic tests | No | No | Yes | Yes | No | Yes | Medium |
| Recursive and reduced form equations | Yes | No | No | Yes | No | No | Low |
| Endogeneity and self selection in panel data | Yes | No | Yes | No | No | No | Low |
| Instrumental variable method | No | No | No | No | No | Yes | Low |
How to read this table. A tick means the topic was set in that sitting and a cross means it was not. High means the topic appeared four or more times, or appeared recently after a gap. Medium means two or three appearances. Low means a single appearance with no repeat, which is worth a glance and nothing more.
The pattern that jumps out is seasonal. Ramsey's RESET test has shown up in June sittings and stayed away from December ones, while Hausman and the identification problem lean the other way. Students preparing for a December sitting should therefore not treat the two lists as interchangeable. The same session by session method sits behind every code we cover in the BAECH Guess Paper series.
How the BECE 142 Applied Econometrics answers are written and checked
Every answer is drafted from the IGNOU block text itself, then cross checked against the wording of the actual question papers before it enters the file. Nothing is paraphrased from a coaching guide and nothing is generated and shipped without a human reading it.
The drafting order is fixed. First the relevant unit is read and the definition sentence is lifted, because the vocabulary in that sentence is what a checker recognises. Then the numbered points are built, keeping to the count the block itself uses, so five limitations of the linear probability model stay five and do not quietly become seven. Finally the answer is trimmed to the word target for its mark weight.
The checking pass looks for three things: a definition in the opening lines, a numbered structure in the middle, and an evaluative closing sentence rather than an abrupt stop. Answers that fail any of the three go back for a rewrite. This is also why the file stays at 13 questions instead of 30. A short list that is written properly beats a long list that is padded.
Course structure, credit weight and unit titles are verified against the official course listing for the IGNOU Bachelor of Arts (Honours) Economics programme (BAECH) before any page like this is published, so the block and unit mapping in the table above reflects the syllabus you are actually studying.
What not to prepare for the BECE 142 Applied Econometrics exam
Five categories of content can be dropped from your revision for this paper, and dropping them buys back roughly a week. This list is as much a part of the guess paper as the answers are.
- Heavy derivations and proofs. The paper rewards conceptual description. You are asked to analyse the case of simultaneous equation bias, not to derive the probability limit of the OLS estimator line by line.
- Line by line software code. Understand the sequence of R and Stata commands and what each one produces. Memorising exact syntax is not what the 12 marks are for.
- One off topics with no repeat. Instrumental variable conditions and recursive models have surfaced once each in six papers. Read them once and move on.
- Rare short note items. Section C rotates within a fairly narrow pool. Short notes that appeared in a single session and never returned are not worth committing to memory.
- Modern econometrics outside the blocks. Anything not present in the four IGNOU blocks, however standard it is in a textbook elsewhere, cannot be examined here.
The corresponding do list is shorter and blunter. Open with the definition and the scholar's name where the block gives one, such as Ramsey, Hausman, Akaike, Koyck, Nerlove or Cagan. Pair each theory with the book's own example, the cobweb, car ownership, the test score ANOVA. Number your points. Close with two evaluative lines.
Who should order the BECE 142 guess paper with answers
This file suits a student who has limited time, a working schedule, or a re appear in Applied Econometrics, and who wants a defensible shortlist rather than the full 12 unit reading load. It is not a replacement for the IGNOU blocks and we do not pretend otherwise.
It fits you if you are sitting the paper in a few weeks and have not yet opened Block 3 or Block 4. It fits you if you failed the paper earlier and need to know which topics are worth a second run. It fits you if econometric vocabulary is the barrier rather than the economics, since every answer is written in ordinary English with the technical terms explained where they first appear.
It is a poor fit in two situations. If you have an entire semester available and want conceptual mastery, read the blocks and use this only for revision at the end. And if you are hoping for numerical problem solutions with worked arithmetic, this paper is built around the descriptive and analytical questions that dominate the Applied Econometrics sittings, not around computation.
How to get the complete BECE 142 Solved Guess Paper on WhatsApp
Message 9899436384 on WhatsApp with the course code BECE 142 and your exam session, and you will get the price and the delivery details in the same chat. The full 16 page PDF is sent to you there once the enquiry is confirmed. There is no account to create.
- Open WhatsApp and message 9899436384.
- Send the code and session in one line, for example: BECE 142 Applied Econometrics guess paper, December 2026 session.
- Tell us your medium, English or Hindi, so we send the right notes on phrasing.
- Confirm the enquiry and receive the complete PDF with all 13 answers on the same chat.
- Keep the chat open. Doubts on any of the 13 answers are answered on the same number.
Two practical notes. Order early in the session rather than in the last week, because the answers are written to be revised twice, not skimmed once. And save the chat, since it becomes your doubt channel for the rest of your preparation.
Ready to order the complete BECE 142 file for the December 2026 session?
Get the complete BECE 142 guess paper on WhatsApp 9899436384Frequently asked questions about the BECE 142 guess paper with answers
How many questions are in the BECE 142 Applied Econometrics guess paper?
The file carries 13 questions with complete written answers across 13 pages, inside a 16 page PDF. Four are Section A questions worth 20 marks, seven are Section B questions worth 12 marks, and two are short note sets worth 6 plus 6 marks. Five of the 13 answers are printed in full on this page so you can check the standard first.
Which sessions were analysed to build the BECE 142 important questions list?
Six consecutive term end papers were read line by line: June 2023, December 2023, June 2024, December 2024, June 2025 and December 2025. Every topic was marked present or absent for each sitting, which produced the 26 row frequency table on page 16 of the file and reproduced in full on this page. The December 2025 paper, being the most recent one available, carried the heaviest weight in the ranking.
Is the BECE 142 guess paper useful for the December 2026 term end examination?
Yes. It was prepared for the 2026 term end sittings and remains current for December 2026, since IGNOU conducts only June and December examinations for this course. The June 2026 sitting has already been conducted, so December 2026 is the live session this file is aimed at. The high priority topics come from patterns that have held across three years, so the shortlist does not swing session to session.
Does BECE 142 Applied Econometrics have a practical file or project?
No. BECE 142 is a six credit theory course assessed through assignments and a three hour written term end paper. There is no practical file, laboratory record or project submission. Block 4 deals with R, EViews and Stata, but it is examined as a written description of procedure, not as a submitted software file. Students told otherwise have usually confused it with a different BAECH paper.
Can I pass BECE 142 by studying only this guess paper?
It gives you a strong shortlist, not a guarantee. You attempt 8 questions out of 15 printed, and the 13 topics here cover the repeat heavy areas of that pool. Students who also revise the assignment questions and one or two previous papers put themselves in a considerably safer position than those relying on a single document.
Are the BECE 142 answers written in English or Hindi?
The file is written in English. Students appearing in the Hindi medium generally use it for the answer structure, the point ordering and the technical vocabulary, then write the script in Hindi. Mention your medium when you message us and we will send the phrasing notes that help with the translation of key terms, since the econometric vocabulary is standard across both mediums.
How is the BECE 142 guess paper different from the solved assignment?
The assignment is set by the university, changes every academic year and is submitted for internal marks. This guess paper is built from term end question papers and targets the written examination instead. The two overlap on topics such as ILS and panel data, but the wording, mark weights and word limits differ, so prepare them separately rather than assuming one covers the other.
How long does delivery of the BECE 142 guess paper take after I message?
Delivery happens on the same WhatsApp chat once the enquiry is confirmed, usually within working hours on the same day. The file is a single PDF you can open on a phone or laptop. If you need it urgently before a sitting, say so in your first message on 9899436384 and it will be prioritised.