<|begin_of_text|><|start_header_id|>system<|end_header_id|>You are an expert on climate change, human mobility and migration. Answer the question truthfully.<|eot_id|><|start_header_id|>user<|end_header_id|>Here are the title and abstract of a scientific paper probably related to climate change, human mobility and migration..
Title:"Local skill concentrations and district employment growth: a simultaneous equation approach for India."
Abstract:"Spatial concentration of skills has been identified as an important factor that causes differences in regional employment in developed countries. In the light of this literature, this paper investigates the relationship between spatial distribution of skills in the year 2001 and district-wise employment growth between the years 2001 and 2011, for India. We argue that educational attainment as a measure of worker skills may not be appropriate for a developing country and take a different approach to measuring skills wherein a worker's skill is inferred from the occupation in which he/she is employed. We use district-wise data on occupational distribution of employment (from Census of India) along with the skill content of occupations (from a US-based dataset called O-NET) to measure regional skills. Using this measure, we model employment and population growth simultaneously and find a positive relationship between cognitive skills and employment growth. The results are robust across all the models that we employ. Our results suggest the presence of externalities associated with skilled people which is instrumental in increasing productivity and employment in skilled regions.."
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Q1: Is this article is about 'human migration mobility': 1 = yes; 0 = no. Answer with a number. Do not give a textual explanation.

Q2: What drivers of migration and mobility does the article study? 0 = 'other', 1 = 'climate', 2 = 'environment', 3 = 'economic', 4 = 'conflict', 5 = 'political', 6 = 'social', 7 = 'family'. Answer with a number or a sequence of numbers separated by commas. Do not give a textual explanation. 

Q3: What is the overall sentiment of the article?:0 = 'neutral', 1 = 'negative', 2 = 'positive'. Answer with a number. Do not give a textual explanation.

Q4: What type of climate or environmental keywords are explicitly mentioned?:  0 = 'none', 1 = 'algal blooms', 2 = 'infestation', 3 = 'infectious diseases', 4 = 'ocean acidification', 5 = 'sea ice', 6 = 'acid rain', 7 = 'drought', 8 = 'cold wave', 9 = 'heat wave', 10 = 'glacial', 11 = 'wildfire', 12 = 'air pollution', 13 = 'biodiversity loss', 14 = 'coastal erosion', 15 = 'land degradation', 16 = 'deforestation', 17 = 'desertification', 18 = 'water pollution', 19 = 'diebacks', 20 = 'permafrost loss', 21 = 'sand mining', 22 = 'sea level rise', 23 = 'earthquake', 24 = 'tsunami', 25 = 'volcanic', 26 = 'flood', 27 = 'avalanche', 28 = 'landslide', 29 = 'downburst', 30 = 'thunderstorm', 31 = 'sandstorm', 32 = 'haze', 33 = 'storm', 34 = 'cyclone', 35 = 'blizzard', 36 = 'hail', 37 = 'snow', 38 = 'tornado', 39 = 'wind', 40 = 'hurricane', 41 = 'typhoon', 42 = 'other'. Answer with a number or a sequence of numbers separated by commas. Do not give a textual explanation. 

Q5: What discipline does the article belong to?: 0 = 'other', 1 = 'social science', 2 = 'natural science', 3 = 'arts and humanities', 4 = 'multidiscipline and interdiscipline'. Answer with a number. Do not give a textual explanation.

Q6: Does the article apply quantitative and/or statistical analysis?: 0 = 'no', 1 = 'yes'. Answer with a number. Do not give a textual explanation.

Use the following template: 

Q1 = [];
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Q6 = [].<|eot_id|><|start_header_id|>assistant<|end_header_id|>Answer:
Q1 = [0];
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Local skill concentrations and district employment growth: a simultaneous equation approach for India
Spatial concentration of skills has been identified as an important factor that causes differences in regional employment in developed countries. In the light of this literature, this paper investigates the relationship between spatial distribution of skills in the year 2001 and district-wise employment growth between the years 2001 and 2011, for India. We argue that educational attainment as a measure of worker skills may not be appropriate for a developing country and take a different approach to measuring skills wherein a worker's skill is inferred from the occupation in which he/she is employed. We use district-wise data on occupational distribution of employment (from Census of India) along with the skill content of occupations (from a US-based dataset called O-NET) to measure regional skills. Using this measure, we model employment and population growth simultaneously and find a positive relationship between cognitive skills and employment growth. The results are robust across all the models that we employ. Our results suggest the presence of externalities associated with skilled people which is instrumental in increasing productivity and employment in skilled regions.