Consider the following statements : Statement-I : India accounts for 3-2% of global export of goods. Statement-II : Many local companies and some foreign companies operating in India have taken advantage of India's 'Production-linked Incentive' scheme. Which one of the following is correct in respect of the above statements?

States an explicit policy objective: "To double our percentage share of global merchandise trade within the next five years," implying India considers its current share small and that policymakers track that percentage.

A student could take the policy target as motivation to look up (a) India's merchandise export value for 2023 and (b) total world merchandise exports for 2023, then compute India's share and compare to the baseline implicit in the policy.

Notes that "percentage share of India in the global trade is on the lower side," giving qualitative support that India's share is small relative to major traders.

Combine this qualitative judgment with external numeric data (India's 2023 goods exports and global goods export totals) to assess the precise percentage and its relative smallness.

Provides detailed composition and percentage shares of export commodity groups for India (e.g., manufactured goods 65.7% in 2016–17), which helps estimate the structure of India's exports when comparing to global merchandise flows.

A student could use the composition to determine which commodity categories to compare with global category shares (from world trade data) when calculating or cross-checking India's overall merchandise export share for 2023.

Gives recent sectoral information (manufacturing 67.8% of India's exports in 2021–22) and notes competition from China and East Asia, implying the need to consider global leaders when judging India's global share.

Use these sector weights plus known global export values by sector (from international trade statistics) to estimate whether India's overall merchandise share in 2023 is plausibly small or growing.

States an explicit goal to "double India's share in world agri exports" and past baseline ($30+ billion in 2017–18), showing that for specific sectors India tracks shares and values as a route to estimating global share.

A student can use the provided baseline agricultural export value and compare it to world agricultural export totals (external data) to estimate India's agri share, then aggregate sectoral estimates to inform an overall merchandise-share estimate for 2023.

Explains the PLI scheme mechanics, lists initial sectors (mobiles, medical devices, pharmaceuticals) and that the scheme gives 4–6% incentives on incremental domestic sales.

A student could use this to focus data searches on beneficiary lists for these named sectors (government notifications/award lists) to count participating Indian companies by 2023.

The 'Make in India' initiative coordinates action plans across numerous manufacturing sectors (27), indicating a policy environment that could produce many eligible firms for schemes like PLI.

A student could cross-reference the 27 Make in India sectors with PLI-covered sectors to estimate the pool of domestic firms likely to apply for/receive PLI incentives by 2023.

Notes that several top Indian companies benefited from increased competition by investing in technology and production — a pattern suggesting domestic firms can and do take advantage of policy incentives.

Use this pattern to prioritize checking large, technologically capable Indian firms in relevant sectors when compiling counts of PLI beneficiaries.

Points out structural weaknesses (low labour productivity, small unit size) in Indian manufacturing, which may limit how many domestic firms can effectively benefit from schemes.

A student can use this to temper expectations and look for concentration of PLI beneficiaries among larger/organized firms rather than many small units when estimating totals.

Explains what PLI does, lists sectors (mobiles, medical devices, pharmaceuticals) and that scheme is being extended to more 'sunrise' sectors—identifies the types of manufacturers (including multinationals) that could qualify.

A student could list foreign firms active in those sectors in India (e.g., phone OEMs, pharma MNCs) and check publicly announced PLI beneficiaries to estimate how many foreign companies might be included.

Notes removal of earlier restrictions on foreign ownership (FERA → FEMA), meaning foreign-owned companies are treated alike—implying they are eligible to operate and participate in schemes like PLI.

Combine this with sector lists from PLI to expect that foreign-owned subsidiaries present in those sectors could apply for incentives; then cross-check company ownership of known PLI beneficiaries.

Describes FDI routes (automatic/greenfield/brownfield) and that multinationals can set up new factories—relevant because PLI rewards incremental manufacturing in India, which greenfield FDI could supply.

Use knowledge of which foreign firms made greenfield/brownfield investments in PLI-targeted sectors and compare to PLI beneficiary lists to infer foreign company participation.

States DPIIT sets rules for foreign investment and policy pronouncements—DPIIT also administers PLI, so this links the administrative authority over both FDI and incentive schemes.

A student could search DPIIT press releases/notifications (using this clue) for published lists of PLI beneficiaries and identify which are foreign-owned.