Index Numbers and Time Series MCQs 2026

An index number measures

1. Aonly absolute levels without comparison✓
2. Brelative change in a variable or group of variables over time or space✓
3. Conly correlation r✓
4. Donly ANOVA F ratios✓

Laspeyres price index uses weights from

1. Acurrent period quantities only✓
2. Bonly geometric means of prices✓
3. Conly regression residuals✓
4. Dthe base period quantities✓

Paasche price index uses weights from

1. Abase period quantities only✓
2. Bonly fixed 100 weights✓
3. Conly block totals✓
4. Dthe current period quantities✓

Fisher ideal index is

1. Athe arithmetic mean of price relatives only✓
2. Bequal to Paasche only always✓
3. Cthe sum of Laspeyres and Paasche✓
4. Dthe geometric mean of Laspeyres and Paasche indexes✓

Base period in index numbers is

1. Aalways the latest year✓
2. Bthe period with highest price only✓
3. Cthe period assigned index value 100 (or 1) for comparison✓
4. Dthe ANOVA grand mean✓

Price index tracks changes in

1. Aonly physical output quantities without prices✓
2. Bprices of a basket of goods✓
3. Conly wages without prices✓
4. Donly ranks✓

Quantity index tracks changes in

1. Aonly monetary values at current prices✓
2. Bonly seasonal indices✓
3. Cphysical volume or quantity produced/consumed✓
4. Donly residual variance✓

Weighted index numbers are preferred because

1. Aitems differ in economic importance✓
2. Bevery item must receive equal weight✓
3. Cweights eliminate trend✓
4. Dweights equal correlation r✓

Simple (unweighted) price index may use

1. Aonly Laspeyres quantities✓
2. Barithmetic mean of price relatives✓
3. Conly regression slopes✓
4. Donly Mann–Whitney ranks✓

Chain index links

1. Aonly one base forever✓
2. Bonly ANOVA blocks✓
3. Cperiod-to-period relatives rather than fixing one distant base✓
4. Donly non-parametric signs✓

Consumer Price Index (CPI) conceptually measures

1. Aonly wholesale factory prices✓
2. Bonly stock dividends✓
3. Conly block effects✓
4. Daverage change in prices paid by consumers for a market basket✓

Wholesale Price Index (WPI) focuses on

1. Aprices at wholesale/producer stage✓
2. Bretail consumer baskets only✓
3. Conly wage rates✓
4. Donly moving-average seasonality removal✓

A time series is

1. Aonly cross-sectional survey at one date✓
2. Bonly ANOVA treatment table✓
3. Conly correlation matrix✓
4. Ddata recorded sequentially over time✓

Four components of classical time series decomposition are

1. Aonly mean and variance✓
2. Bonly regression residuals✓
3. Conly blocking factors✓
4. Dtrend, seasonal, cyclical and irregular✓

Trend component represents

1. Arepeating within-year pattern only✓
2. Blong-term general movement in the series✓
3. Crandom noise only✓
4. Donly Laspeyres base weights✓

Seasonal component represents

1. Along-term drift only✓
2. Bone-time shocks only✓
3. Conly sampling error in CRD✓
4. Dregular periodic fluctuations within a year (or fixed period)✓

Cyclical component refers to

1. Adaily noise✓
2. Bfluctuations over periods longer than one year, often economy-wide✓
3. Cfixed 12-month seasonality only✓
4. Dthe base year✓

Irregular (random) component captures

1. Athe deterministic trend only✓
2. Bfixed seasonal indices exactly✓
3. Cunpredictable short-term variation✓
4. Dthe Laspeyres formula✓

Simple moving average smooths a series by

1. Aaveraging values over a fixed window of consecutive periods✓
2. Bsquaring each observation✓
3. Cusing only base-year weights✓
4. Dranking observations✓

Centered moving average is used especially to

1. Acompute Pearson r only✓
2. Btest homogeneity of variance✓
3. Creplace randomization in CRD✓
4. Destimate trend when seasonality is present✓

Weighted moving average assigns

1. Aequal weight only always✓
2. Bdifferent weights to observations in the window✓
3. Czero weight to all but one point always✓
4. Donly ranks✓

Seasonal indices express

1. Aonly long-run slope✓
2. Btypical percentage departure from trend in each season✓
3. Conly block means✓
4. Donly K–S distance✓

Deseasonalizing data means

1. Aadding seasonality✓
2. Bconverting to Laspeyres only✓
3. Cremoving estimated seasonal effects to reveal trend and irregular✓
4. Dreplacing Y with ranks✓

Ratio-to-moving-average method estimates seasonal factors by

1. Amultiplying by Paasche only✓
2. Busing sign test✓
3. Cdividing actual values by moving-average trend values✓
4. Dcomputing SS_between✓

Linear trend equation Yₜ = a + bt estimates trend using

1. Aleast squares over time t✓
2. Bonly sign test✓
3. Conly CRD blocking✓
4. Donly Fisher index✓

Semi-average method splits the series into halves and uses

1. AWilcoxon ranks✓
2. Baverages of each half to fit a trend line✓
3. CANOVA F only✓
4. DK–S CDF✓

Shifting base of an index means

1. Achanging the reference period to a more recent one✓
2. Beliminating weights✓
3. Cfixing r at zero✓
4. Ddropping seasonal component✓

Time reversal test (Fisher) requires

1. Aonly Paasche to satisfy always✓
2. Bprice index formula gives reciprocal when time periods are reversed✓
3. Conly block SS to match✓
4. Donly runs randomness✓

Factor reversal test requires

1. Aonly Laspeyres price index passes always✓
2. Bproduct of price and quantity indexes equals value index✓
3. Conly seasonal index passes✓
4. Donly sign test passes✓

Cost of living index aims to measure

1. Aonly factory output volume✓
2. Bonly correlation✓
3. Conly error MS✓
4. Dchange in expenditure needed to maintain a standard of living✓

Deflating nominal values uses

1. APaasche quantity only without prices✓
2. Bsign test✓
3. Ca price index to express values in constant-price terms✓
4. DLSD comparison✓

Inflation is often measured by

1. Aonly moving-average window length✓
2. Bonly block variance✓
3. Cpercentage change in a general price index such as CPI✓
4. Donly partial correlation✓

Laspeyres index tends to

1. Aoverstate price change when consumers substitute away from dearer goods✓
2. Bunderstate always when substitution occurs✓
3. Cequal Paasche always✓
4. Dignore base quantities✓

Paasche index tends to

1. Aoverstate always✓
2. Buse only base weights✓
3. Cunderstate price change due to substitution at current quantities✓
4. Dignore current quantities✓

Fisher index is considered ideal because it

1. Auses only unweighted relatives✓
2. Bsatisfies time reversal and factor reversal tests✓
3. Cignores quantities✓
4. Dequals Laspeyres always✓

Link relatives chain

1. Aeach period to the immediately preceding period✓
2. Bonly to a distant fixed base✓
3. Conly through ANOVA✓
4. Donly via sign test✓

Fixed-base index compares every period to

1. Aonly the previous period always✓
2. Bone constant base period✓
3. Conly block means✓
4. Donly residual e✓

Limitations of index numbers include

1. Athey are always unique and unbiased✓
2. Bchoice of basket, weights and base can affect results✓
3. Cthey eliminate seasonality automatically✓
4. Dthey prove causation✓

Detrending a series removes

1. Aall data permanently✓
2. Bonly irregular only✓
3. Cestimated trend to study cyclical or seasonal patterns✓
4. Donly base year✓

Exponential smoothing assigns

1. Aequal weights to all history✓
2. Bonly ranks✓
3. Cdeclining weights to older observations in computing forecasts✓
4. Donly block labels✓

Stationarity in time series roughly means

1. Astatistical properties do not change over time✓
2. Btrend always increases✓
3. Cseasonality is absent always✓
4. Dvariance is infinite✓

Autocorrelation in time series measures

1. Aonly cross-sectional Pearson r✓
2. Bonly Mann–Whitney U✓
3. Conly LSD✓
4. Dcorrelation of the series with its own lagged values✓

Lag k value means

1. Athe value k periods before the current time✓
2. Bthe seasonal index only✓
3. Cthe block mean✓
4. Dthe grand mean in ANOVA✓

Seasonal adjustment in official statistics aims to

1. Aremove predictable seasonal movement for trend analysis✓
2. Badd noise✓
3. Creplace Fisher with Laspeyres only✓
4. Deliminate all variation✓

Composite index combines

1. Aseveral items or sub-indexes into one overall measure✓
2. Bonly one commodity always✓
3. Conly regression intercept✓
4. Donly one ANOVA factor✓

Aggregate method in index construction uses

1. Aonly ranks✓
2. Bonly runs✓
3. Ctotal price or quantity of the basket directly✓
4. Donly partial F✓

Average of price relatives computes index from

1. Amean of individual item price ratios✓
2. Bonly quantity weights from future✓
3. Conly SS_within✓
4. Donly Wilcoxon statistic✓

Moving average length for monthly seasonal data is often

1. A12 months✓
2. B3 months only always✓
3. Cequal to sample size n✓
4. Dzero✓

Irregular fluctuations may arise from

1. Adeterministic seasonal pattern✓
2. Bfixed trend slope only✓
3. CLaspeyres base alone✓
4. Dstrikes, wars, policy shocks or measurement error✓

Index number problem of choice of average means

1. Aall formulas always agree✓
2. Bindexes never use weights✓
3. Cindexes replace time series✓
4. Ddifferent formulas (L, P, F) give different answers✓